GPT-5 vs O3 vs GPT-4.1, Which one is better for Penetration Testing
Comparing GPT-5, GPT-4.1, and o3 for Login API Penetration Testing
We tested three GPT models — GPT-5, GPT-4.1, and o3 — to evaluate their ability to generate penetration testing scenarios for a login API. We evaluated them across:
Coverage – How many security categories do they address
Specificity / Actionability – How clear and usable the scenarios are
Safety / Ethics – Whether the output can be safely shared
Organization / Usability – Clarity, grouping, and lack of redundancy
Remediation Friendliness – How easily developers can act on the findings
We tested three GPT models — GPT-5, GPT-4.1, and o3 — to evaluate their ability to generate penetration testing scenarios for a login API. We evaluated them across:
Coverage – How many security categories do they address
Specificity / Actionability – How clear and usable the scenarios are
Safety / Ethics – Whether the output can be safely shared
Organization / Usability – Clarity, grouping, and lack of redundancy
Remediation Friendliness – How easily developers can act on the findings
We tested three GPT models — GPT-5, GPT-4.1, and o3 — to evaluate their ability to generate penetration testing scenarios for a login API. We evaluated them across:
Coverage – How many security categories do they address
Specificity / Actionability – How clear and usable the scenarios are
Safety / Ethics – Whether the output can be safely shared
Organization / Usability – Clarity, grouping, and lack of redundancy
Remediation Friendliness – How easily developers can act on the findings
Key Findings
GPT-5: Broadest coverage and most technical depth — ideal for building a master pentest scope after sanitizing unsafe payloads.
GPT-4.1: Safest and most concise checklist for developers — but missing depth in some key areas.
o3: Balanced coverage across categories — but some unsafe examples and less organized output.
GPT-5: Broadest coverage and most technical depth — ideal for building a master pentest scope after sanitizing unsafe payloads.
GPT-4.1: Safest and most concise checklist for developers — but missing depth in some key areas.
o3: Balanced coverage across categories — but some unsafe examples and less organized output.
GPT-5: Broadest coverage and most technical depth — ideal for building a master pentest scope after sanitizing unsafe payloads.
GPT-4.1: Safest and most concise checklist for developers — but missing depth in some key areas.
o3: Balanced coverage across categories — but some unsafe examples and less organized output.
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Category Coverage
Category | GPT-5 (Count/Quality) | GPT-4.1 (Count/Quality) | o3 (Count/Quality) |
|---|---|---|---|
BOLA / IDOR | 3 / High | 1 / Medium | 1 / High |
Info Disclosure | 9 / High | 1 / Medium | 2 / High |
Rate Limiting / Brute Force / DoS | 11 / High | 1 / Medium | 2 / Medium |
Function-Level Authorization | 4 / High | 1 / Medium | 2 / High |
Mass Assignment | 3 / High | 1 / Medium | 3 / High |
CORS Misconfiguration | 4 / High | 1 / High | 1 / High |
Verbose Errors / Debug Exposure | 4 / High | 2 / Medium | 2 / Medium |
TLS / HTTPS / Cookie Security | 5 / High | 0 / — | 1 / High |
Injection Attacks | 8 / High | 1 / Medium | 4 / Medium |
Legacy / Deprecated Endpoints | 7 / High | 1 / Medium | 2 / Medium |
Logging & Monitoring Gaps | 8 / High | 1 / Low | 1 / Medium |
Misc Misconfigurations | 2 / High | 1 / Medium | 1 / Medium |
Category | GPT-5 (Count/Quality) | GPT-4.1 (Count/Quality) | o3 (Count/Quality) |
|---|---|---|---|
BOLA / IDOR | 3 / High | 1 / Medium | 1 / High |
Info Disclosure | 9 / High | 1 / Medium | 2 / High |
Rate Limiting / Brute Force / DoS | 11 / High | 1 / Medium | 2 / Medium |
Function-Level Authorization | 4 / High | 1 / Medium | 2 / High |
Mass Assignment | 3 / High | 1 / Medium | 3 / High |
CORS Misconfiguration | 4 / High | 1 / High | 1 / High |
Verbose Errors / Debug Exposure | 4 / High | 2 / Medium | 2 / Medium |
TLS / HTTPS / Cookie Security | 5 / High | 0 / — | 1 / High |
Injection Attacks | 8 / High | 1 / Medium | 4 / Medium |
Legacy / Deprecated Endpoints | 7 / High | 1 / Medium | 2 / Medium |
Logging & Monitoring Gaps | 8 / High | 1 / Low | 1 / Medium |
Misc Misconfigurations | 2 / High | 1 / Medium | 1 / Medium |
Category | GPT-5 (Count/Quality) | GPT-4.1 (Count/Quality) | o3 (Count/Quality) |
|---|---|---|---|
BOLA / IDOR | 3 / High | 1 / Medium | 1 / High |
Info Disclosure | 9 / High | 1 / Medium | 2 / High |
Rate Limiting / Brute Force / DoS | 11 / High | 1 / Medium | 2 / Medium |
Function-Level Authorization | 4 / High | 1 / Medium | 2 / High |
Mass Assignment | 3 / High | 1 / Medium | 3 / High |
CORS Misconfiguration | 4 / High | 1 / High | 1 / High |
Verbose Errors / Debug Exposure | 4 / High | 2 / Medium | 2 / Medium |
TLS / HTTPS / Cookie Security | 5 / High | 0 / — | 1 / High |
Injection Attacks | 8 / High | 1 / Medium | 4 / Medium |
Legacy / Deprecated Endpoints | 7 / High | 1 / Medium | 2 / Medium |
Logging & Monitoring Gaps | 8 / High | 1 / Low | 1 / Medium |
Misc Misconfigurations | 2 / High | 1 / Medium | 1 / Medium |
Total Coverage
GPT-5: 56 scenarios, 12/12 categories, High quality
GPT-4.1: 12 scenarios, 9/12 categories, Medium quality
o3: 17 scenarios, 12/12 categories, Medium–High quality
GPT-5: 56 scenarios, 12/12 categories, High quality
GPT-4.1: 12 scenarios, 9/12 categories, Medium quality
o3: 17 scenarios, 12/12 categories, Medium–High quality
GPT-5: 56 scenarios, 12/12 categories, High quality
GPT-4.1: 12 scenarios, 9/12 categories, Medium quality
o3: 17 scenarios, 12/12 categories, Medium–High quality
Model-by-Model Breakdown
GPT-5 — Depth & Breadth
56 scenarios covering all 12 categories.
Detailed tests for BOLA, excessive data exposure, brute-force, rate-limit bypass, mass assignment, CORS issues, TLS weaknesses, injections (SQL, NoSQL, LDAP), legacy endpoints, misconfigurations, and post-authentication logging gaps.
Strengths: Full coverage, detailed, and realistic tests, including detection gaps.
Weaknesses: Verbose, some destructive payloads, needs severity tags and grouping.
GPT-5 Scenarios
Overview: GPT-5 produced 56 scenarios covering all 12 categories, with high depth, realistic exploit ideas, and post-authentication detection gaps. Excellent for red teams after removing unsafe payloads.BOLA / IDOR
BOLA / IDOR
1. POST to the login api with valid credentials and an added tenant_id set to another organization’s ID; the API issues a token scoped to that tenant and returns that organization’s user profile data, exposing unauthorized information via object identifier manipulation (BOLA).
2. POST to the login api adding a user_id field referencing another account alongside valid email/password; the API binds the session to that user and returns their details, demonstrating BOLA from tampered object identifiers.
3. POST to the login api with an impersonate_user_id pointing to another user; the API authenticates and returns a session and user object for that ID, leaking unauthorized data through manipulated object identifiers (BOLA).
Info Disclosure
4. Using the login api, submit valid email/password and verify whether the success response returns only an auth token or also exposes the full user object with PII (user_id, email, phone, roles), last_login_ip, and internal timestamps, indicating excessive data exposure.
5. Send a valid email with an incorrect password to the login api and inspect the error payload for unnecessary details such as account existence, lock status, last_login_at, or password_age that aid user enumeration.
6. After successful authentication via the login api, decode the returned token and check for excessive claims (email, phone, address, permissions, org_id, debug flags) that are not required by the client.
7. Authenticate through the login api and review the response body for sensitive security attributes inadvertently serialized (password_hash, password_salt, mfa_secret, recovery_codes), which should never be returned.
8. Attempt the login api request with common expansion selectors (expand=* or fields=*) and observe whether the response includes full profile, billing, or permissions data beyond the minimal token, exposing unnecessary information.
9. Examine the login api response for leakage of internal correlation identifiers (user internal IDs, tenant IDs) or session metadata not needed by clients that could facilitate pivoting or privilege mapping.
10. login api: Flood the unauthenticated endpoint with hundreds of POST requests per second for the same email using a password wordlist; absence of per-IP or per-account throttling and no 429 responses enable brute-force login.
Rate Limiting / Brute Force / DoS
11. login api: Perform credential stuffing by attempting a few password guesses across thousands of emails in parallel; if aggregate limits are not enforced and attempts are processed without slowdown or blocking, large-scale automated logins are feasible.
12. login api: Open multiple persistent connections (Connection: keep-alive) and issue thousands of concurrent, well-formed JSON login requests with Accept and Accept-Encoding headers set; if the service does not cap concurrency or return 429, it can be overwhelmed, degrading availability.
13. login api: Send periodic traffic spikes (e.g., 1000 login attempts in a 10-second burst) to test burst rate limiting; acceptance of bursts without throttling indicates ineffective sliding-window controls.
14. login api: Rapidly submit login requests for a large list of emails with an invalid password to probe username existence; lack of request-per-minute limits permits high-volume enumeration and can exhaust resources.
Function-Level Authorization
15. As a regular user, call the login api and include an undocumented 'scope':'admin' (or 'role':'admin') field; if an admin-scoped token is returned, a restricted function is exposed due to missing function-level authorization.
16. As a normal user, call the login api with an 'impersonate_user_id' parameter; if the API issues a token for that user without verifying admin privileges, the impersonation function lacks proper authorization.
17. Invoke the login api with 'skip_mfa': true (or 'trusted_device': true) to trigger an internal-only MFA bypass; if authentication succeeds without MFA for a non-privileged user, function-level authorization is broken.
18. Use the login api to request a service token by passing 'client_type':'internal' or 'grant_type':'client_credentials'; if granted to a regular user, restricted authentication modes are accessible due to inadequate function-level authorization.
Mass Assignment
19. For login api, submit a valid email/password along with unexpected attributes (e.g., is_admin: true, role: 'admin', two_factor_bypass: true) in the JSON payload; verify whether the backend’s model binding persists these fields to the user/session and returns an admin-scoped token, indicating a mass assignment flaw.
20. For login api, include account state fields (e.g., confirmed: true, email_verified: true, locked: false) in the sign-in payload; check whether the user’s profile reflects these unauthorized updates after authentication, demonstrating mass assignment.
21. For login api, append session-related fields (e.g., scopes: ['admin'], token_expires_at: '2099-12-31T23:59:59Z', trusted_device: true) to the request body; if the issued token inherits these values, it reveals mass assignment on session properties.
CORS Misconfiguration
22. From an untrusted origin, attempt a credentialed cross-origin XHR to the login api; if permissive CORS reflects arbitrary Origin and allows credentials, the response can be read and tokens exfiltrated.
Verbose Errors / Debug Exposure
23. Induce authentication failures and review responses from the login api; verbose messages or stack traces enable user enumeration and reveal backend details.
TLS / HTTPS / Cookie Security
24. Test transport security on the login api; if plain HTTP or deprecated TLS versions/ciphers are accepted, credentials can be intercepted via downgrade or network attacks.
25. After login, inspect cookies issued by the login api; missing Secure, HttpOnly, or SameSite flags allow JavaScript access or cross-site requests to steal or fixate the session.
Misc Misconfigurations:
26. Probe the login api for HTTP TRACE; if enabled, cross-site tracing can reflect sensitive headers such as Authorization or Cookie, causing information disclosure.
27. Send permissive CORS preflights to the login api with arbitrary custom headers and methods; if allowed, a malicious site can perform authenticated cross-origin requests and read responses.
Legacy / Deprecated Endpoints
28. Enumerate non-documented routes on the login api; exposed debug, actuator, or metrics endpoints may leak configuration, environment variables, or secrets.
29. Attempt HTTP method overrides against the login api; if GET is accepted for login via X-HTTP-Method-Override or _method, credentials may leak through logs and caches.
30. Inspect response headers from the login api for server/framework version disclosure; use leaked versions to assess known vulnerabilities for targeted exploitation.
31. Verify HSTS on the login api; absent or lax HSTS enables SSL stripping or mixed-content downgrade to capture credentials.
32. Identify publicly reachable staging or test instances of the login api with relaxed controls; exposed endpoints or default settings may allow token retrieval or user enumeration.
33. Send malformed or oversized JSON to the login api; verbose parser errors that reveal file paths, class names, or configuration values aid targeted exploitation.
34. Set Origin to null in cross-origin requests to the login api; acceptance indicates overly permissive CORS that enables token theft from sandboxed or local-file contexts.
Injection Attacks
35. Attempt SQL authentication bypass by injecting ' OR '1'='1 into the email field on login api; if a token is issued without valid credentials, SQL injection is present.
36. Perform time-based SQL injection by placing a delay function payload in the password value on login api and measuring consistent response delays, indicating backend query execution.
37. Trigger error-based SQLi by submitting an email like test@example.com' to login api and observing verbose database errors or stack traces, confirming injectable string concatenation.
38. Attempt NoSQL operator injection on login api by sending the password as a JSON object using $ne (e.g., password: {$ne: null}) to check for authentication bypass due to improper type validation.
39. Attempt NoSQL regex injection by supplying the email as an object with $regex (e.g., email: {$regex: '^admin$', $options: 'i'}) in login api to bypass exact matches.
40. Test LDAP injection on login api by setting the email to a crafted filter such as admin*)(|(uid=*)) and any password, and observe unexpected authentication or LDAP error responses due to unsafe filter construction.
41. Conduct blind SQL injection on login api by comparing responses for email values embedding boolean conditions (e.g., 'admin' AND '1'='1' vs 'admin' AND '1'='2'); differential outcomes indicate injection.
42. Probe query-builder injection on login api by adding unexpected operators like $or alongside email and password to see if naive filters are merged into the authentication query.
Legacy / Deprecated Endpoints
43. Use Accept: application/vnd.qodex.v1+json with the login api to negotiate a deprecated version; if it returns an auth token or distinct legacy errors, an unretired v1 is exposed.
44. Include X-API-Version: 1 when calling the login api and perform rapid repeated attempts; lack of lockout or throttling compared to current behavior indicates an active untracked legacy implementation.
45. Submit a form-encoded payload with fields username and pass to the login api instead of JSON email and password; successful processing reveals a backward-compatible legacy path left enabled.
46. Reach the staging instance of the login api and observe verbose stack traces or debug tokens, confirming a publicly reachable outdated build due to incomplete asset inventory.
47. Send OPTIONS/HEAD to the login api and inspect response headers for legacy identifiers (for example, X-Powered-By with a deprecated framework); presence indicates an unmanaged older version still deployed.
48. Call the login api without currently required headers (Accept, Accept-Encoding, Connection); if the request is accepted, it suggests fallback to an older, less strict code path still exposed.
Logging & Monitoring Gaps
49. login api: Execute a credential-stuffing run of 1,000 login attempts across many accounts; verify that only HTTP 401s are returned and no security logs capture per-account failure counts, source IPs, or user agents, leaving the attack undetected.
50. login api: Perform a successful login from an unusual IP and geography for a dormant account; confirm that the service logs neither the source IP/geo nor a token issuance audit event, and no alert is raised, delaying detection of unauthorized access.
51. login api: Submit login requests for 500 non-existent emails; check that the system does not log the spike of invalid-user attempts or the targeted identifiers, preventing reconnaissance detection.
52. login api: Attempt one password guess against 1,000 known user emails (password spraying); observe that only generic 401 responses occur with no aggregated failure events, IP correlation, or threshold alerts in logs.
53. login api: Flood with malformed JSON and oversized payloads to simulate automated scanning; verify that only error responses occur and that no structured security logs record client IP, payload size, or validation error types, keeping the probe invisible.
54. login api: Repeatedly attempt logins to a disabled or locked account; confirm that logs omit the account status and do not escalate repeated attempts from the same IP, hindering detection of targeted abuse.
55. login api: After a successful login, attempt to trace the session in logs; note the absence of request-to-session correlation (no request ID linked to user ID or token metadata) and no timestamped audit entry for token creation, impeding investigation.
56. login api: Generate sustained high-rate login traffic from multiple IPs; validate that logs lack aggregation by user or IP and no alerts reflect the surge, delaying recognition of an ongoing attack.
GPT-5 — Depth & Breadth
56 scenarios covering all 12 categories.
Detailed tests for BOLA, excessive data exposure, brute-force, rate-limit bypass, mass assignment, CORS issues, TLS weaknesses, injections (SQL, NoSQL, LDAP), legacy endpoints, misconfigurations, and post-authentication logging gaps.
Strengths: Full coverage, detailed, and realistic tests, including detection gaps.
Weaknesses: Verbose, some destructive payloads, needs severity tags and grouping.
GPT-5 Scenarios
Overview: GPT-5 produced 56 scenarios covering all 12 categories, with high depth, realistic exploit ideas, and post-authentication detection gaps. Excellent for red teams after removing unsafe payloads.BOLA / IDOR
BOLA / IDOR
1. POST to the login api with valid credentials and an added tenant_id set to another organization’s ID; the API issues a token scoped to that tenant and returns that organization’s user profile data, exposing unauthorized information via object identifier manipulation (BOLA).
2. POST to the login api adding a user_id field referencing another account alongside valid email/password; the API binds the session to that user and returns their details, demonstrating BOLA from tampered object identifiers.
3. POST to the login api with an impersonate_user_id pointing to another user; the API authenticates and returns a session and user object for that ID, leaking unauthorized data through manipulated object identifiers (BOLA).
Info Disclosure
4. Using the login api, submit valid email/password and verify whether the success response returns only an auth token or also exposes the full user object with PII (user_id, email, phone, roles), last_login_ip, and internal timestamps, indicating excessive data exposure.
5. Send a valid email with an incorrect password to the login api and inspect the error payload for unnecessary details such as account existence, lock status, last_login_at, or password_age that aid user enumeration.
6. After successful authentication via the login api, decode the returned token and check for excessive claims (email, phone, address, permissions, org_id, debug flags) that are not required by the client.
7. Authenticate through the login api and review the response body for sensitive security attributes inadvertently serialized (password_hash, password_salt, mfa_secret, recovery_codes), which should never be returned.
8. Attempt the login api request with common expansion selectors (expand=* or fields=*) and observe whether the response includes full profile, billing, or permissions data beyond the minimal token, exposing unnecessary information.
9. Examine the login api response for leakage of internal correlation identifiers (user internal IDs, tenant IDs) or session metadata not needed by clients that could facilitate pivoting or privilege mapping.
10. login api: Flood the unauthenticated endpoint with hundreds of POST requests per second for the same email using a password wordlist; absence of per-IP or per-account throttling and no 429 responses enable brute-force login.
Rate Limiting / Brute Force / DoS
11. login api: Perform credential stuffing by attempting a few password guesses across thousands of emails in parallel; if aggregate limits are not enforced and attempts are processed without slowdown or blocking, large-scale automated logins are feasible.
12. login api: Open multiple persistent connections (Connection: keep-alive) and issue thousands of concurrent, well-formed JSON login requests with Accept and Accept-Encoding headers set; if the service does not cap concurrency or return 429, it can be overwhelmed, degrading availability.
13. login api: Send periodic traffic spikes (e.g., 1000 login attempts in a 10-second burst) to test burst rate limiting; acceptance of bursts without throttling indicates ineffective sliding-window controls.
14. login api: Rapidly submit login requests for a large list of emails with an invalid password to probe username existence; lack of request-per-minute limits permits high-volume enumeration and can exhaust resources.
Function-Level Authorization
15. As a regular user, call the login api and include an undocumented 'scope':'admin' (or 'role':'admin') field; if an admin-scoped token is returned, a restricted function is exposed due to missing function-level authorization.
16. As a normal user, call the login api with an 'impersonate_user_id' parameter; if the API issues a token for that user without verifying admin privileges, the impersonation function lacks proper authorization.
17. Invoke the login api with 'skip_mfa': true (or 'trusted_device': true) to trigger an internal-only MFA bypass; if authentication succeeds without MFA for a non-privileged user, function-level authorization is broken.
18. Use the login api to request a service token by passing 'client_type':'internal' or 'grant_type':'client_credentials'; if granted to a regular user, restricted authentication modes are accessible due to inadequate function-level authorization.
Mass Assignment
19. For login api, submit a valid email/password along with unexpected attributes (e.g., is_admin: true, role: 'admin', two_factor_bypass: true) in the JSON payload; verify whether the backend’s model binding persists these fields to the user/session and returns an admin-scoped token, indicating a mass assignment flaw.
20. For login api, include account state fields (e.g., confirmed: true, email_verified: true, locked: false) in the sign-in payload; check whether the user’s profile reflects these unauthorized updates after authentication, demonstrating mass assignment.
21. For login api, append session-related fields (e.g., scopes: ['admin'], token_expires_at: '2099-12-31T23:59:59Z', trusted_device: true) to the request body; if the issued token inherits these values, it reveals mass assignment on session properties.
CORS Misconfiguration
22. From an untrusted origin, attempt a credentialed cross-origin XHR to the login api; if permissive CORS reflects arbitrary Origin and allows credentials, the response can be read and tokens exfiltrated.
Verbose Errors / Debug Exposure
23. Induce authentication failures and review responses from the login api; verbose messages or stack traces enable user enumeration and reveal backend details.
TLS / HTTPS / Cookie Security
24. Test transport security on the login api; if plain HTTP or deprecated TLS versions/ciphers are accepted, credentials can be intercepted via downgrade or network attacks.
25. After login, inspect cookies issued by the login api; missing Secure, HttpOnly, or SameSite flags allow JavaScript access or cross-site requests to steal or fixate the session.
Misc Misconfigurations:
26. Probe the login api for HTTP TRACE; if enabled, cross-site tracing can reflect sensitive headers such as Authorization or Cookie, causing information disclosure.
27. Send permissive CORS preflights to the login api with arbitrary custom headers and methods; if allowed, a malicious site can perform authenticated cross-origin requests and read responses.
Legacy / Deprecated Endpoints
28. Enumerate non-documented routes on the login api; exposed debug, actuator, or metrics endpoints may leak configuration, environment variables, or secrets.
29. Attempt HTTP method overrides against the login api; if GET is accepted for login via X-HTTP-Method-Override or _method, credentials may leak through logs and caches.
30. Inspect response headers from the login api for server/framework version disclosure; use leaked versions to assess known vulnerabilities for targeted exploitation.
31. Verify HSTS on the login api; absent or lax HSTS enables SSL stripping or mixed-content downgrade to capture credentials.
32. Identify publicly reachable staging or test instances of the login api with relaxed controls; exposed endpoints or default settings may allow token retrieval or user enumeration.
33. Send malformed or oversized JSON to the login api; verbose parser errors that reveal file paths, class names, or configuration values aid targeted exploitation.
34. Set Origin to null in cross-origin requests to the login api; acceptance indicates overly permissive CORS that enables token theft from sandboxed or local-file contexts.
Injection Attacks
35. Attempt SQL authentication bypass by injecting ' OR '1'='1 into the email field on login api; if a token is issued without valid credentials, SQL injection is present.
36. Perform time-based SQL injection by placing a delay function payload in the password value on login api and measuring consistent response delays, indicating backend query execution.
37. Trigger error-based SQLi by submitting an email like test@example.com' to login api and observing verbose database errors or stack traces, confirming injectable string concatenation.
38. Attempt NoSQL operator injection on login api by sending the password as a JSON object using $ne (e.g., password: {$ne: null}) to check for authentication bypass due to improper type validation.
39. Attempt NoSQL regex injection by supplying the email as an object with $regex (e.g., email: {$regex: '^admin$', $options: 'i'}) in login api to bypass exact matches.
40. Test LDAP injection on login api by setting the email to a crafted filter such as admin*)(|(uid=*)) and any password, and observe unexpected authentication or LDAP error responses due to unsafe filter construction.
41. Conduct blind SQL injection on login api by comparing responses for email values embedding boolean conditions (e.g., 'admin' AND '1'='1' vs 'admin' AND '1'='2'); differential outcomes indicate injection.
42. Probe query-builder injection on login api by adding unexpected operators like $or alongside email and password to see if naive filters are merged into the authentication query.
Legacy / Deprecated Endpoints
43. Use Accept: application/vnd.qodex.v1+json with the login api to negotiate a deprecated version; if it returns an auth token or distinct legacy errors, an unretired v1 is exposed.
44. Include X-API-Version: 1 when calling the login api and perform rapid repeated attempts; lack of lockout or throttling compared to current behavior indicates an active untracked legacy implementation.
45. Submit a form-encoded payload with fields username and pass to the login api instead of JSON email and password; successful processing reveals a backward-compatible legacy path left enabled.
46. Reach the staging instance of the login api and observe verbose stack traces or debug tokens, confirming a publicly reachable outdated build due to incomplete asset inventory.
47. Send OPTIONS/HEAD to the login api and inspect response headers for legacy identifiers (for example, X-Powered-By with a deprecated framework); presence indicates an unmanaged older version still deployed.
48. Call the login api without currently required headers (Accept, Accept-Encoding, Connection); if the request is accepted, it suggests fallback to an older, less strict code path still exposed.
Logging & Monitoring Gaps
49. login api: Execute a credential-stuffing run of 1,000 login attempts across many accounts; verify that only HTTP 401s are returned and no security logs capture per-account failure counts, source IPs, or user agents, leaving the attack undetected.
50. login api: Perform a successful login from an unusual IP and geography for a dormant account; confirm that the service logs neither the source IP/geo nor a token issuance audit event, and no alert is raised, delaying detection of unauthorized access.
51. login api: Submit login requests for 500 non-existent emails; check that the system does not log the spike of invalid-user attempts or the targeted identifiers, preventing reconnaissance detection.
52. login api: Attempt one password guess against 1,000 known user emails (password spraying); observe that only generic 401 responses occur with no aggregated failure events, IP correlation, or threshold alerts in logs.
53. login api: Flood with malformed JSON and oversized payloads to simulate automated scanning; verify that only error responses occur and that no structured security logs record client IP, payload size, or validation error types, keeping the probe invisible.
54. login api: Repeatedly attempt logins to a disabled or locked account; confirm that logs omit the account status and do not escalate repeated attempts from the same IP, hindering detection of targeted abuse.
55. login api: After a successful login, attempt to trace the session in logs; note the absence of request-to-session correlation (no request ID linked to user ID or token metadata) and no timestamped audit entry for token creation, impeding investigation.
56. login api: Generate sustained high-rate login traffic from multiple IPs; validate that logs lack aggregation by user or IP and no alerts reflect the surge, delaying recognition of an ongoing attack.
GPT-5 — Depth & Breadth
56 scenarios covering all 12 categories.
Detailed tests for BOLA, excessive data exposure, brute-force, rate-limit bypass, mass assignment, CORS issues, TLS weaknesses, injections (SQL, NoSQL, LDAP), legacy endpoints, misconfigurations, and post-authentication logging gaps.
Strengths: Full coverage, detailed, and realistic tests, including detection gaps.
Weaknesses: Verbose, some destructive payloads, needs severity tags and grouping.
GPT-5 Scenarios
Overview: GPT-5 produced 56 scenarios covering all 12 categories, with high depth, realistic exploit ideas, and post-authentication detection gaps. Excellent for red teams after removing unsafe payloads.BOLA / IDOR
BOLA / IDOR
1. POST to the login api with valid credentials and an added tenant_id set to another organization’s ID; the API issues a token scoped to that tenant and returns that organization’s user profile data, exposing unauthorized information via object identifier manipulation (BOLA).
2. POST to the login api adding a user_id field referencing another account alongside valid email/password; the API binds the session to that user and returns their details, demonstrating BOLA from tampered object identifiers.
3. POST to the login api with an impersonate_user_id pointing to another user; the API authenticates and returns a session and user object for that ID, leaking unauthorized data through manipulated object identifiers (BOLA).
Info Disclosure
4. Using the login api, submit valid email/password and verify whether the success response returns only an auth token or also exposes the full user object with PII (user_id, email, phone, roles), last_login_ip, and internal timestamps, indicating excessive data exposure.
5. Send a valid email with an incorrect password to the login api and inspect the error payload for unnecessary details such as account existence, lock status, last_login_at, or password_age that aid user enumeration.
6. After successful authentication via the login api, decode the returned token and check for excessive claims (email, phone, address, permissions, org_id, debug flags) that are not required by the client.
7. Authenticate through the login api and review the response body for sensitive security attributes inadvertently serialized (password_hash, password_salt, mfa_secret, recovery_codes), which should never be returned.
8. Attempt the login api request with common expansion selectors (expand=* or fields=*) and observe whether the response includes full profile, billing, or permissions data beyond the minimal token, exposing unnecessary information.
9. Examine the login api response for leakage of internal correlation identifiers (user internal IDs, tenant IDs) or session metadata not needed by clients that could facilitate pivoting or privilege mapping.
10. login api: Flood the unauthenticated endpoint with hundreds of POST requests per second for the same email using a password wordlist; absence of per-IP or per-account throttling and no 429 responses enable brute-force login.
Rate Limiting / Brute Force / DoS
11. login api: Perform credential stuffing by attempting a few password guesses across thousands of emails in parallel; if aggregate limits are not enforced and attempts are processed without slowdown or blocking, large-scale automated logins are feasible.
12. login api: Open multiple persistent connections (Connection: keep-alive) and issue thousands of concurrent, well-formed JSON login requests with Accept and Accept-Encoding headers set; if the service does not cap concurrency or return 429, it can be overwhelmed, degrading availability.
13. login api: Send periodic traffic spikes (e.g., 1000 login attempts in a 10-second burst) to test burst rate limiting; acceptance of bursts without throttling indicates ineffective sliding-window controls.
14. login api: Rapidly submit login requests for a large list of emails with an invalid password to probe username existence; lack of request-per-minute limits permits high-volume enumeration and can exhaust resources.
Function-Level Authorization
15. As a regular user, call the login api and include an undocumented 'scope':'admin' (or 'role':'admin') field; if an admin-scoped token is returned, a restricted function is exposed due to missing function-level authorization.
16. As a normal user, call the login api with an 'impersonate_user_id' parameter; if the API issues a token for that user without verifying admin privileges, the impersonation function lacks proper authorization.
17. Invoke the login api with 'skip_mfa': true (or 'trusted_device': true) to trigger an internal-only MFA bypass; if authentication succeeds without MFA for a non-privileged user, function-level authorization is broken.
18. Use the login api to request a service token by passing 'client_type':'internal' or 'grant_type':'client_credentials'; if granted to a regular user, restricted authentication modes are accessible due to inadequate function-level authorization.
Mass Assignment
19. For login api, submit a valid email/password along with unexpected attributes (e.g., is_admin: true, role: 'admin', two_factor_bypass: true) in the JSON payload; verify whether the backend’s model binding persists these fields to the user/session and returns an admin-scoped token, indicating a mass assignment flaw.
20. For login api, include account state fields (e.g., confirmed: true, email_verified: true, locked: false) in the sign-in payload; check whether the user’s profile reflects these unauthorized updates after authentication, demonstrating mass assignment.
21. For login api, append session-related fields (e.g., scopes: ['admin'], token_expires_at: '2099-12-31T23:59:59Z', trusted_device: true) to the request body; if the issued token inherits these values, it reveals mass assignment on session properties.
CORS Misconfiguration
22. From an untrusted origin, attempt a credentialed cross-origin XHR to the login api; if permissive CORS reflects arbitrary Origin and allows credentials, the response can be read and tokens exfiltrated.
Verbose Errors / Debug Exposure
23. Induce authentication failures and review responses from the login api; verbose messages or stack traces enable user enumeration and reveal backend details.
TLS / HTTPS / Cookie Security
24. Test transport security on the login api; if plain HTTP or deprecated TLS versions/ciphers are accepted, credentials can be intercepted via downgrade or network attacks.
25. After login, inspect cookies issued by the login api; missing Secure, HttpOnly, or SameSite flags allow JavaScript access or cross-site requests to steal or fixate the session.
Misc Misconfigurations:
26. Probe the login api for HTTP TRACE; if enabled, cross-site tracing can reflect sensitive headers such as Authorization or Cookie, causing information disclosure.
27. Send permissive CORS preflights to the login api with arbitrary custom headers and methods; if allowed, a malicious site can perform authenticated cross-origin requests and read responses.
Legacy / Deprecated Endpoints
28. Enumerate non-documented routes on the login api; exposed debug, actuator, or metrics endpoints may leak configuration, environment variables, or secrets.
29. Attempt HTTP method overrides against the login api; if GET is accepted for login via X-HTTP-Method-Override or _method, credentials may leak through logs and caches.
30. Inspect response headers from the login api for server/framework version disclosure; use leaked versions to assess known vulnerabilities for targeted exploitation.
31. Verify HSTS on the login api; absent or lax HSTS enables SSL stripping or mixed-content downgrade to capture credentials.
32. Identify publicly reachable staging or test instances of the login api with relaxed controls; exposed endpoints or default settings may allow token retrieval or user enumeration.
33. Send malformed or oversized JSON to the login api; verbose parser errors that reveal file paths, class names, or configuration values aid targeted exploitation.
34. Set Origin to null in cross-origin requests to the login api; acceptance indicates overly permissive CORS that enables token theft from sandboxed or local-file contexts.
Injection Attacks
35. Attempt SQL authentication bypass by injecting ' OR '1'='1 into the email field on login api; if a token is issued without valid credentials, SQL injection is present.
36. Perform time-based SQL injection by placing a delay function payload in the password value on login api and measuring consistent response delays, indicating backend query execution.
37. Trigger error-based SQLi by submitting an email like test@example.com' to login api and observing verbose database errors or stack traces, confirming injectable string concatenation.
38. Attempt NoSQL operator injection on login api by sending the password as a JSON object using $ne (e.g., password: {$ne: null}) to check for authentication bypass due to improper type validation.
39. Attempt NoSQL regex injection by supplying the email as an object with $regex (e.g., email: {$regex: '^admin$', $options: 'i'}) in login api to bypass exact matches.
40. Test LDAP injection on login api by setting the email to a crafted filter such as admin*)(|(uid=*)) and any password, and observe unexpected authentication or LDAP error responses due to unsafe filter construction.
41. Conduct blind SQL injection on login api by comparing responses for email values embedding boolean conditions (e.g., 'admin' AND '1'='1' vs 'admin' AND '1'='2'); differential outcomes indicate injection.
42. Probe query-builder injection on login api by adding unexpected operators like $or alongside email and password to see if naive filters are merged into the authentication query.
Legacy / Deprecated Endpoints
43. Use Accept: application/vnd.qodex.v1+json with the login api to negotiate a deprecated version; if it returns an auth token or distinct legacy errors, an unretired v1 is exposed.
44. Include X-API-Version: 1 when calling the login api and perform rapid repeated attempts; lack of lockout or throttling compared to current behavior indicates an active untracked legacy implementation.
45. Submit a form-encoded payload with fields username and pass to the login api instead of JSON email and password; successful processing reveals a backward-compatible legacy path left enabled.
46. Reach the staging instance of the login api and observe verbose stack traces or debug tokens, confirming a publicly reachable outdated build due to incomplete asset inventory.
47. Send OPTIONS/HEAD to the login api and inspect response headers for legacy identifiers (for example, X-Powered-By with a deprecated framework); presence indicates an unmanaged older version still deployed.
48. Call the login api without currently required headers (Accept, Accept-Encoding, Connection); if the request is accepted, it suggests fallback to an older, less strict code path still exposed.
Logging & Monitoring Gaps
49. login api: Execute a credential-stuffing run of 1,000 login attempts across many accounts; verify that only HTTP 401s are returned and no security logs capture per-account failure counts, source IPs, or user agents, leaving the attack undetected.
50. login api: Perform a successful login from an unusual IP and geography for a dormant account; confirm that the service logs neither the source IP/geo nor a token issuance audit event, and no alert is raised, delaying detection of unauthorized access.
51. login api: Submit login requests for 500 non-existent emails; check that the system does not log the spike of invalid-user attempts or the targeted identifiers, preventing reconnaissance detection.
52. login api: Attempt one password guess against 1,000 known user emails (password spraying); observe that only generic 401 responses occur with no aggregated failure events, IP correlation, or threshold alerts in logs.
53. login api: Flood with malformed JSON and oversized payloads to simulate automated scanning; verify that only error responses occur and that no structured security logs record client IP, payload size, or validation error types, keeping the probe invisible.
54. login api: Repeatedly attempt logins to a disabled or locked account; confirm that logs omit the account status and do not escalate repeated attempts from the same IP, hindering detection of targeted abuse.
55. login api: After a successful login, attempt to trace the session in logs; note the absence of request-to-session correlation (no request ID linked to user ID or token metadata) and no timestamped audit entry for token creation, impeding investigation.
56. login api: Generate sustained high-rate login traffic from multiple IPs; validate that logs lack aggregation by user or IP and no alerts reflect the surge, delaying recognition of an ongoing attack.
O3 — Practical Middle Ground
17 scenarios covering all categories.
Mix of access control flaws, excessive data exposure, verbose errors, CORS, weak transport security, brute-force, DoS, mass assignment, SQL/command injection, legacy endpoints, and logging gaps.
Strengths: Balanced depth, practical scenarios.
Weaknesses: Unsafe explicit examples, weaker organization, and less post-exploitation focus.
o3 Scenarios:
Overview: o3 generated 17 scenarios covering all categories with balanced depth, but some unsafe explicit payloads and less post-exploitation focus.
BOLA / Access Control
1. Send a crafted POST request to the login api that includes a forged \"user_id\" field set to another user’s identifier alongside any password; if the backend prioritizes the identifier over proper credential verification, the response returns a valid authentication token for the targeted account, demonstrating Broken Object Level Authorization.
Info Disclosure
2. Send a valid email and password to login api, then inspect the JSON response to confirm whether it returns the entire user object—including password_hash, is_admin status, and internal_id—alongside the auth token, thereby exposing sensitive fields unnecessary for authentication.
3. Provide an incorrect password to login api and review the error payload; if it reveals details such as account existence, lockout counter, or password expiry date instead of a generic error, the endpoint is exposing excessive information useful for attackers.
Rate Limiting / DoS
4. login api: Flood the endpoint with 10,000 POST requests per minute using a single IP and varying password guesses for the same email; verify that the service never throttles or blocks the requests, confirming absent rate-limiting and enabling credential brute-forcing.
5. login api: Launch 5,000 concurrent POST requests containing large, malformed JSON bodies to rapidly consume CPU and memory; observe that the endpoint processes all requests without delay or rejection, evidencing missing resource limits that could facilitate a denial-of-service attack.
Mass Assignment / Privilege Escalation
6. Send a POST request to the login api using valid user credentials while injecting an extra JSON field \"role\":\"admin\"; if the backend fails to validate roles server-side, the user is authenticated with elevated administrator privileges, allowing unauthorized access to restricted functions.
7. Send a login api request with correct email and password but include extra JSON fields such as \\\"role\\\":\\\"admin\\\" and \\\"is_superuser\\\":true to test if mass assignment silently upgrades the user’s privileges on successful authentication.
8. Invoke the login api with an additional \\\"email_confirmed\\\":true property in the payload to check whether the server improperly marks the account as verified during the sign-in process.
9. Submit a login api request appending\\\"account_status\\\":\\\"premium\\\" and \\\"subscription_end\\\":\\\"2099-12-31\\\" parameters to evaluate if unauthorized subscription attributes are assigned through mass assignment.
Verbose Errors / Debug
10. login api: Send a malformed JSON body to the unauthenticated login endpoint and observe verbose 500 error responses that disclose Ruby on Rails version, file paths, and database details, confirming improper error handling configuration.
CORS & TLS
11. login api: From a malicious domain, issue an XMLHttpRequest with credentials to the login endpoint; the wildcard CORS header ‘Access-Control-Allow-Origin: *’ combined with ‘Access-Control-Allow-Credentials: true’ accepts the request, exposing user credentials due to lax CORS configuration.
12. login api: Attempt to POST credentials over plain HTTP instead of HTTPS; the endpoint accepts the request without redirecting or enforcing TLS, demonstrating transport layer misconfiguration that enables credential sniffing.
Injection Attacks
13. login api: Attempt SQL injection by sending the email field value \"admin@example.com' OR '1'='1\" with any password, checking if authentication is bypassed due to unsanitized SQL concatenation.
14. login api: Submit the email value \"user@example.com'); DROP TABLE users;--\" in the JSON payload to test for stacked SQL query execution that could delete critical data.
15. login api: Provide the password value \"$(ping attacker.com)\" to detect potential command injection if the backend passes credentials to shell commands without proper sanitization.
Legacy Endpoints
16. Probe legacy paths (e.g., v1/login api) and observe that the deprecated login api still accepts credentials and returns JWTs without rate-limiting headers, demonstrating Improper Assets Management where an untracked version exposes weaker security controls.
Logging & Monitoring Gaps
17. Perform 50 rapid failed authentication attempts against the login api using random email/password combinations and verify that no authentication failure logs are written to the central log store and no alerting thresholds are triggered, demonstrating insufficient logging and monitoring that allows brute-force attacks to proceed undetected.
17 scenarios covering all categories.
Mix of access control flaws, excessive data exposure, verbose errors, CORS, weak transport security, brute-force, DoS, mass assignment, SQL/command injection, legacy endpoints, and logging gaps.
Strengths: Balanced depth, practical scenarios.
Weaknesses: Unsafe explicit examples, weaker organization, and less post-exploitation focus.
o3 Scenarios:
Overview: o3 generated 17 scenarios covering all categories with balanced depth, but some unsafe explicit payloads and less post-exploitation focus.
BOLA / Access Control
1. Send a crafted POST request to the login api that includes a forged \"user_id\" field set to another user’s identifier alongside any password; if the backend prioritizes the identifier over proper credential verification, the response returns a valid authentication token for the targeted account, demonstrating Broken Object Level Authorization.
Info Disclosure
2. Send a valid email and password to login api, then inspect the JSON response to confirm whether it returns the entire user object—including password_hash, is_admin status, and internal_id—alongside the auth token, thereby exposing sensitive fields unnecessary for authentication.
3. Provide an incorrect password to login api and review the error payload; if it reveals details such as account existence, lockout counter, or password expiry date instead of a generic error, the endpoint is exposing excessive information useful for attackers.
Rate Limiting / DoS
4. login api: Flood the endpoint with 10,000 POST requests per minute using a single IP and varying password guesses for the same email; verify that the service never throttles or blocks the requests, confirming absent rate-limiting and enabling credential brute-forcing.
5. login api: Launch 5,000 concurrent POST requests containing large, malformed JSON bodies to rapidly consume CPU and memory; observe that the endpoint processes all requests without delay or rejection, evidencing missing resource limits that could facilitate a denial-of-service attack.
Mass Assignment / Privilege Escalation
6. Send a POST request to the login api using valid user credentials while injecting an extra JSON field \"role\":\"admin\"; if the backend fails to validate roles server-side, the user is authenticated with elevated administrator privileges, allowing unauthorized access to restricted functions.
7. Send a login api request with correct email and password but include extra JSON fields such as \\\"role\\\":\\\"admin\\\" and \\\"is_superuser\\\":true to test if mass assignment silently upgrades the user’s privileges on successful authentication.
8. Invoke the login api with an additional \\\"email_confirmed\\\":true property in the payload to check whether the server improperly marks the account as verified during the sign-in process.
9. Submit a login api request appending\\\"account_status\\\":\\\"premium\\\" and \\\"subscription_end\\\":\\\"2099-12-31\\\" parameters to evaluate if unauthorized subscription attributes are assigned through mass assignment.
Verbose Errors / Debug
10. login api: Send a malformed JSON body to the unauthenticated login endpoint and observe verbose 500 error responses that disclose Ruby on Rails version, file paths, and database details, confirming improper error handling configuration.
CORS & TLS
11. login api: From a malicious domain, issue an XMLHttpRequest with credentials to the login endpoint; the wildcard CORS header ‘Access-Control-Allow-Origin: *’ combined with ‘Access-Control-Allow-Credentials: true’ accepts the request, exposing user credentials due to lax CORS configuration.
12. login api: Attempt to POST credentials over plain HTTP instead of HTTPS; the endpoint accepts the request without redirecting or enforcing TLS, demonstrating transport layer misconfiguration that enables credential sniffing.
Injection Attacks
13. login api: Attempt SQL injection by sending the email field value \"admin@example.com' OR '1'='1\" with any password, checking if authentication is bypassed due to unsanitized SQL concatenation.
14. login api: Submit the email value \"user@example.com'); DROP TABLE users;--\" in the JSON payload to test for stacked SQL query execution that could delete critical data.
15. login api: Provide the password value \"$(ping attacker.com)\" to detect potential command injection if the backend passes credentials to shell commands without proper sanitization.
Legacy Endpoints
16. Probe legacy paths (e.g., v1/login api) and observe that the deprecated login api still accepts credentials and returns JWTs without rate-limiting headers, demonstrating Improper Assets Management where an untracked version exposes weaker security controls.
Logging & Monitoring Gaps
17. Perform 50 rapid failed authentication attempts against the login api using random email/password combinations and verify that no authentication failure logs are written to the central log store and no alerting thresholds are triggered, demonstrating insufficient logging and monitoring that allows brute-force attacks to proceed undetected.
17 scenarios covering all categories.
Mix of access control flaws, excessive data exposure, verbose errors, CORS, weak transport security, brute-force, DoS, mass assignment, SQL/command injection, legacy endpoints, and logging gaps.
Strengths: Balanced depth, practical scenarios.
Weaknesses: Unsafe explicit examples, weaker organization, and less post-exploitation focus.
o3 Scenarios:
Overview: o3 generated 17 scenarios covering all categories with balanced depth, but some unsafe explicit payloads and less post-exploitation focus.
BOLA / Access Control
1. Send a crafted POST request to the login api that includes a forged \"user_id\" field set to another user’s identifier alongside any password; if the backend prioritizes the identifier over proper credential verification, the response returns a valid authentication token for the targeted account, demonstrating Broken Object Level Authorization.
Info Disclosure
2. Send a valid email and password to login api, then inspect the JSON response to confirm whether it returns the entire user object—including password_hash, is_admin status, and internal_id—alongside the auth token, thereby exposing sensitive fields unnecessary for authentication.
3. Provide an incorrect password to login api and review the error payload; if it reveals details such as account existence, lockout counter, or password expiry date instead of a generic error, the endpoint is exposing excessive information useful for attackers.
Rate Limiting / DoS
4. login api: Flood the endpoint with 10,000 POST requests per minute using a single IP and varying password guesses for the same email; verify that the service never throttles or blocks the requests, confirming absent rate-limiting and enabling credential brute-forcing.
5. login api: Launch 5,000 concurrent POST requests containing large, malformed JSON bodies to rapidly consume CPU and memory; observe that the endpoint processes all requests without delay or rejection, evidencing missing resource limits that could facilitate a denial-of-service attack.
Mass Assignment / Privilege Escalation
6. Send a POST request to the login api using valid user credentials while injecting an extra JSON field \"role\":\"admin\"; if the backend fails to validate roles server-side, the user is authenticated with elevated administrator privileges, allowing unauthorized access to restricted functions.
7. Send a login api request with correct email and password but include extra JSON fields such as \\\"role\\\":\\\"admin\\\" and \\\"is_superuser\\\":true to test if mass assignment silently upgrades the user’s privileges on successful authentication.
8. Invoke the login api with an additional \\\"email_confirmed\\\":true property in the payload to check whether the server improperly marks the account as verified during the sign-in process.
9. Submit a login api request appending\\\"account_status\\\":\\\"premium\\\" and \\\"subscription_end\\\":\\\"2099-12-31\\\" parameters to evaluate if unauthorized subscription attributes are assigned through mass assignment.
Verbose Errors / Debug
10. login api: Send a malformed JSON body to the unauthenticated login endpoint and observe verbose 500 error responses that disclose Ruby on Rails version, file paths, and database details, confirming improper error handling configuration.
CORS & TLS
11. login api: From a malicious domain, issue an XMLHttpRequest with credentials to the login endpoint; the wildcard CORS header ‘Access-Control-Allow-Origin: *’ combined with ‘Access-Control-Allow-Credentials: true’ accepts the request, exposing user credentials due to lax CORS configuration.
12. login api: Attempt to POST credentials over plain HTTP instead of HTTPS; the endpoint accepts the request without redirecting or enforcing TLS, demonstrating transport layer misconfiguration that enables credential sniffing.
Injection Attacks
13. login api: Attempt SQL injection by sending the email field value \"admin@example.com' OR '1'='1\" with any password, checking if authentication is bypassed due to unsanitized SQL concatenation.
14. login api: Submit the email value \"user@example.com'); DROP TABLE users;--\" in the JSON payload to test for stacked SQL query execution that could delete critical data.
15. login api: Provide the password value \"$(ping attacker.com)\" to detect potential command injection if the backend passes credentials to shell commands without proper sanitization.
Legacy Endpoints
16. Probe legacy paths (e.g., v1/login api) and observe that the deprecated login api still accepts credentials and returns JWTs without rate-limiting headers, demonstrating Improper Assets Management where an untracked version exposes weaker security controls.
Logging & Monitoring Gaps
17. Perform 50 rapid failed authentication attempts against the login api using random email/password combinations and verify that no authentication failure logs are written to the central log store and no alerting thresholds are triggered, demonstrating insufficient logging and monitoring that allows brute-force attacks to proceed undetected.
GPT-4.1 — Concise & Safe
12 scenarios covering 9 categories.
Focused on broken access control, data exposure, brute-force, function-level privilege bypass, mass assignment, CORS misconfigurations, verbose errors, outdated endpoints, and basic injection.
Strengths: Compact, developer-friendly, safe to share, minimal redundancy.
Weaknesses: Missing TLS/cookie security, logging gaps, advanced injection cases, and post-exploit detection guidance.
GPT-4.1 Scenarios:
Overview: o3 generated 17 scenarios covering all categories with balanced depth, but some unsafe explicit payloads and less post-exploitation focus.BOLA / Access Control
1. Attempt to access another user's account by modifying the email parameter in the request body of the login api to an email address not owned by the testing user, verifying if the API fails to properly restrict authentication or returns unauthorized user data.
2. Test if the login api returns additional user details (such as full profile, roles, or session data) in its response beyond the intended authentication token, thus exposing unnecessary sensitive information on successful login.
3. Send a high volume of login api requests in rapid succession without rate limiting to determine if the lack of resource restrictions allows an attacker to perform brute-force password attacks or overwhelm the authentication mechanism.
4. Attempt to access the 'login api' endpoint with a valid user token and additional admin-specific payload options in the request body to verify if the API permits execution of privileged actions (such as triggering admin-only login flows) due to inadequate function level authorization checks.
5. Test whether the login api is vulnerable to mass assignment by submitting additional fields (e.g., admin: true) in the login request body to attempt unauthorized privilege escalation or alteration of user properties.
6. The login api exposes verbose error messages containing stack traces or authentication logic details when invalid email or password is provided, potentially assisting attackers in crafting further attacks.
7. The login api is deployed with default debug mode enabled, allowing unauthenticated users to access sensitive debugging information via special headers or parameters.
8. The login api CORS policy is set to allow requests from any origin, increasing the risk of credential theft via cross-site scripting from untrusted domains.
9. The login api exposes internal implementation endpoints not meant for public access, such as health checks, due to improper route configuration.
10. Test the login api by submitting a crafted email parameter such as 'admin@example.com' OR 1=1; -- and observe if improper SQL input validation allows bypassing authentication or reveals database errors, indicating an injection vulnerability.
11. Test if deprecated versions of the login api are still accessible, allowing attackers to use outdated authentication methods that may contain known vulnerabilities or lack necessary security checks due to improper assets management.
12. Test scenario for login api: Attempt multiple failed logins with incorrect passwords and verify that the login api does not generate detailed logs for these authentication failures, making it difficult to detect brute-force or credential stuffing attacks in real time.
12 scenarios covering 9 categories.
Focused on broken access control, data exposure, brute-force, function-level privilege bypass, mass assignment, CORS misconfigurations, verbose errors, outdated endpoints, and basic injection.
Strengths: Compact, developer-friendly, safe to share, minimal redundancy.
Weaknesses: Missing TLS/cookie security, logging gaps, advanced injection cases, and post-exploit detection guidance.
GPT-4.1 Scenarios:
Overview: o3 generated 17 scenarios covering all categories with balanced depth, but some unsafe explicit payloads and less post-exploitation focus.BOLA / Access Control
1. Attempt to access another user's account by modifying the email parameter in the request body of the login api to an email address not owned by the testing user, verifying if the API fails to properly restrict authentication or returns unauthorized user data.
2. Test if the login api returns additional user details (such as full profile, roles, or session data) in its response beyond the intended authentication token, thus exposing unnecessary sensitive information on successful login.
3. Send a high volume of login api requests in rapid succession without rate limiting to determine if the lack of resource restrictions allows an attacker to perform brute-force password attacks or overwhelm the authentication mechanism.
4. Attempt to access the 'login api' endpoint with a valid user token and additional admin-specific payload options in the request body to verify if the API permits execution of privileged actions (such as triggering admin-only login flows) due to inadequate function level authorization checks.
5. Test whether the login api is vulnerable to mass assignment by submitting additional fields (e.g., admin: true) in the login request body to attempt unauthorized privilege escalation or alteration of user properties.
6. The login api exposes verbose error messages containing stack traces or authentication logic details when invalid email or password is provided, potentially assisting attackers in crafting further attacks.
7. The login api is deployed with default debug mode enabled, allowing unauthenticated users to access sensitive debugging information via special headers or parameters.
8. The login api CORS policy is set to allow requests from any origin, increasing the risk of credential theft via cross-site scripting from untrusted domains.
9. The login api exposes internal implementation endpoints not meant for public access, such as health checks, due to improper route configuration.
10. Test the login api by submitting a crafted email parameter such as 'admin@example.com' OR 1=1; -- and observe if improper SQL input validation allows bypassing authentication or reveals database errors, indicating an injection vulnerability.
11. Test if deprecated versions of the login api are still accessible, allowing attackers to use outdated authentication methods that may contain known vulnerabilities or lack necessary security checks due to improper assets management.
12. Test scenario for login api: Attempt multiple failed logins with incorrect passwords and verify that the login api does not generate detailed logs for these authentication failures, making it difficult to detect brute-force or credential stuffing attacks in real time.
12 scenarios covering 9 categories.
Focused on broken access control, data exposure, brute-force, function-level privilege bypass, mass assignment, CORS misconfigurations, verbose errors, outdated endpoints, and basic injection.
Strengths: Compact, developer-friendly, safe to share, minimal redundancy.
Weaknesses: Missing TLS/cookie security, logging gaps, advanced injection cases, and post-exploit detection guidance.
GPT-4.1 Scenarios:
Overview: o3 generated 17 scenarios covering all categories with balanced depth, but some unsafe explicit payloads and less post-exploitation focus.BOLA / Access Control
1. Attempt to access another user's account by modifying the email parameter in the request body of the login api to an email address not owned by the testing user, verifying if the API fails to properly restrict authentication or returns unauthorized user data.
2. Test if the login api returns additional user details (such as full profile, roles, or session data) in its response beyond the intended authentication token, thus exposing unnecessary sensitive information on successful login.
3. Send a high volume of login api requests in rapid succession without rate limiting to determine if the lack of resource restrictions allows an attacker to perform brute-force password attacks or overwhelm the authentication mechanism.
4. Attempt to access the 'login api' endpoint with a valid user token and additional admin-specific payload options in the request body to verify if the API permits execution of privileged actions (such as triggering admin-only login flows) due to inadequate function level authorization checks.
5. Test whether the login api is vulnerable to mass assignment by submitting additional fields (e.g., admin: true) in the login request body to attempt unauthorized privilege escalation or alteration of user properties.
6. The login api exposes verbose error messages containing stack traces or authentication logic details when invalid email or password is provided, potentially assisting attackers in crafting further attacks.
7. The login api is deployed with default debug mode enabled, allowing unauthenticated users to access sensitive debugging information via special headers or parameters.
8. The login api CORS policy is set to allow requests from any origin, increasing the risk of credential theft via cross-site scripting from untrusted domains.
9. The login api exposes internal implementation endpoints not meant for public access, such as health checks, due to improper route configuration.
10. Test the login api by submitting a crafted email parameter such as 'admin@example.com' OR 1=1; -- and observe if improper SQL input validation allows bypassing authentication or reveals database errors, indicating an injection vulnerability.
11. Test if deprecated versions of the login api are still accessible, allowing attackers to use outdated authentication methods that may contain known vulnerabilities or lack necessary security checks due to improper assets management.
12. Test scenario for login api: Attempt multiple failed logins with incorrect passwords and verify that the login api does not generate detailed logs for these authentication failures, making it difficult to detect brute-force or credential stuffing attacks in real time.
Scoring
Model | Coverage | Specificity | Safety | Organization | Remediation | Overall |
|---|---|---|---|---|---|---|
GPT-5 | 9/10 | 8/10 | 6/10 | 6/10 | 7/10 | 8/10 |
GPT-4.1 | 6/10 | 7/10 | 8/10 | 8/10 | 6/10 | 7/10 |
o3 | 7/10 | 7/10 | 5/10 | 6/10 | 6/10 | 6.5/10 |
Model | Coverage | Specificity | Safety | Organization | Remediation | Overall |
|---|---|---|---|---|---|---|
GPT-5 | 9/10 | 8/10 | 6/10 | 6/10 | 7/10 | 8/10 |
GPT-4.1 | 6/10 | 7/10 | 8/10 | 8/10 | 6/10 | 7/10 |
o3 | 7/10 | 7/10 | 5/10 | 6/10 | 6/10 | 6.5/10 |
Model | Coverage | Specificity | Safety | Organization | Remediation | Overall |
|---|---|---|---|---|---|---|
GPT-5 | 9/10 | 8/10 | 6/10 | 6/10 | 7/10 | 8/10 |
GPT-4.1 | 6/10 | 7/10 | 8/10 | 8/10 | 6/10 | 7/10 |
o3 | 7/10 | 7/10 | 5/10 | 6/10 | 6/10 | 6.5/10 |
Final Verdict
For red teams / pentesters: Use GPT-5 for full coverage and technical realism — but sanitize before use.
For blue teams / developers: GPT-4.1 is best as a safe, quick-hardening checklist.
For mixed audiences: Start with GPT-4.1 for remediation, then expand with GPT-5.
For red teams / pentesters: Use GPT-5 for full coverage and technical realism — but sanitize before use.
For blue teams / developers: GPT-4.1 is best as a safe, quick-hardening checklist.
For mixed audiences: Start with GPT-4.1 for remediation, then expand with GPT-5.
For red teams / pentesters: Use GPT-5 for full coverage and technical realism — but sanitize before use.
For blue teams / developers: GPT-4.1 is best as a safe, quick-hardening checklist.
For mixed audiences: Start with GPT-4.1 for remediation, then expand with GPT-5.
At Qodex.ai, we bridge the gap between cutting-edge AI models and practical cybersecurity needs. Whether you’re using GPT-5, O3, or GPT-4.1, our platform integrates these AI capabilities into streamlined penetration testing workflows — helping security teams automate reconnaissance, detect vulnerabilities faster, and generate actionable remediation plans.
With Qodex.ai, you get:
AI-powered vulnerability scanning & exploitation simulations
Intelligent reporting tailored for technical & non-technical stakeholders
Real-time insights to strengthen security posture before attackers strike
From proof-of-concept to production-ready security, Qodex.ai ensures your penetration testing is faster, smarter, and more accurate — so you can focus on staying ahead of threats, not chasing them.
At Qodex.ai, we bridge the gap between cutting-edge AI models and practical cybersecurity needs. Whether you’re using GPT-5, O3, or GPT-4.1, our platform integrates these AI capabilities into streamlined penetration testing workflows — helping security teams automate reconnaissance, detect vulnerabilities faster, and generate actionable remediation plans.
With Qodex.ai, you get:
AI-powered vulnerability scanning & exploitation simulations
Intelligent reporting tailored for technical & non-technical stakeholders
Real-time insights to strengthen security posture before attackers strike
From proof-of-concept to production-ready security, Qodex.ai ensures your penetration testing is faster, smarter, and more accurate — so you can focus on staying ahead of threats, not chasing them.
At Qodex.ai, we bridge the gap between cutting-edge AI models and practical cybersecurity needs. Whether you’re using GPT-5, O3, or GPT-4.1, our platform integrates these AI capabilities into streamlined penetration testing workflows — helping security teams automate reconnaissance, detect vulnerabilities faster, and generate actionable remediation plans.
With Qodex.ai, you get:
AI-powered vulnerability scanning & exploitation simulations
Intelligent reporting tailored for technical & non-technical stakeholders
Real-time insights to strengthen security posture before attackers strike
From proof-of-concept to production-ready security, Qodex.ai ensures your penetration testing is faster, smarter, and more accurate — so you can focus on staying ahead of threats, not chasing them.
FAQs
Why should you choose Qodex.ai?
Why should you choose Qodex.ai?
Why should you choose Qodex.ai?
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Discover, Test, and Secure your APIs — 10x Faster.
Product
All Rights Reserved.
Copyright © 2025 Qodex
Discover, Test, and Secure your APIs — 10x Faster.
Product
All Rights Reserved.
Copyright © 2025 Qodex