Severe false positives in Codex cybersecurity request filtering
What issue are you seeing?
Codex's cybersecurity request filtering mechanism has a high false-positive rate for legitimate software engineering and research tasks.
Requests related to topics such as static analysis, fuzz testing, compiler/program analysis, debugging, vulnerability detection, and dynamic binary translation are sometimes incorrectly classified as cybersecurity-related requests, even when the intent is defensive research, software testing, or improving software quality.
This behavior interrupts normal development and research workflows and requires repeated clarification of benign intent.
What steps can reproduce the bug?
- Start a Codex conversation for a legitimate software engineering or research task.
- Ask questions involving security-related concepts, such as analyzing software bugs, testing security tools, fuzzing, static analysis, or debugging program behavior.
- Observe that Codex may trigger cybersecurity-related restrictions or warnings even though the request does not involve exploitation, unauthorized access, or malicious activity.
- Continue the conversation and provide additional context showing the defensive/research purpose; the request may still be incorrectly flagged.
What is the expected behavior?
Codex should distinguish legitimate software engineering and security research from malicious cybersecurity requests.
The safety mechanism should consider the broader context and user intent, rather than relying too heavily on individual keywords or security-related terminology.
Legitimate activities such as debugging, fuzz testing, static analysis research, vulnerability detection, and security tool evaluation should be allowed when they are performed for defensive or academic purposes.
Additional information
This is not a report of a security vulnerability. It is feedback about false positives in the cybersecurity request filtering system.
I understand the importance of cybersecurity safeguards and appreciate the need for abuse prevention. However, the current behavior makes Codex difficult to use for legitimate software engineering and academic research workflows.
Improving contextual understanding and providing clearer explanations or a verification mechanism for legitimate users would significantly improve the experience.
Examples of affected areas include:
- Static analyzer evaluation and bug finding
- Compiler and program analysis research
- Fuzz testing frameworks
- Dynamic binary translation testing
- Debugging and security tool evaluation
5 Comments
Potential duplicates detected. Please review them and close your issue if it is a duplicate.
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I'm experiencing the same problem, and honestly, this is extremely frustrating.
Codex repeatedly classified completely benign local software-development work as a cybersecurity request. I was testing my own Unreal Engine Editor plugin on my own machine, using local assets and local tooling. There were no external targets, network operations, vulnerabilities, exploits, unauthorized access, or security-related objectives of any kind.
Despite explicitly explaining that context, ordinary requests about reproducing an editor failure, compiling an asset, and validating its state were still blocked. Once these additional checks started, they appeared repeatedly and effectively stopped the development session.
A safety system that blocks legitimate work based on broad terminology such as "failure," "sequence," "plugin call," or "crash" is producing too many false positives. Telling affected users to apply for cybersecurity Trusted Access is especially inappropriate when the work has nothing to do with cybersecurity.
This needs more than advice to rephrase requests. Users should not have to carefully sanitize normal engineering terminology to continue working. OpenAI needs to improve the classification, provide a meaningful appeal path, and prevent one false positive from disrupting subsequent unrelated requests across an entire session or account.
I understand your frustration. I have encountered similar false positives in legitimate software development and research scenarios.
You can try using the
/feedbackcommand when this happens, which may help reduce these cases over time. However, I agree that users should not need to constantly rephrase normal engineering requests. The system should improve its contextual understanding to better distinguish legitimate development and research from actual cybersecurity abuse.I can start narrowing this if there’s a concrete repro: what model name/toolset produced the false positive and which phrase set triggered it? If you can provide one representative full user→assistant turn sequence (redacted), I can help map a rule/heuristic mismatch likely causing the repeated blocks.
For my specific case:
Environment:
The false positive occurred when Codex attempted to call a benign MCP tool that only renamed a UMG widget:
ProbeWidget -> RenamedProbeWidget
The tool call was stopped by Codex's cybersecurity safety layer before it reached the local MCP server. No networking, security testing, vulnerability research, or exploitation was involved.
Repeating the same widget-renaming workflow with neutral asset/widget names succeeded, so the word “Probe” may have contributed to the classification. That is only an observation, not a confirmed root cause.
The displayed message was:
"This content can't be shown. We take extra caution with cybersecurity requests. If you're a security professional, you may be able to apply for Trusted Access."