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
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
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.
How qodex.ai helps
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.
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Discover, Test, and Secure your APIs — 10x Faster.
Product
All Rights Reserved.
Copyright © 2025 Qodex