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Agent Refuses Valid Request Due to Excessive Caution — Over-Refusal

Symptom

  • Security researcher asks about a known CVE — agent refuses as “potentially harmful”
  • Developer asks to write error handling for failed auth — agent refuses as “security risk”
  • Agent adds excessive warnings to every code snippet about “use with caution”
  • Legitimate penetration testing workflow blocked by safety filters
  • Agent hedges with “I can’t help with that” for clearly benign technical questions

Root Cause

Without clear context about the user’s role and intent, the model errs toward caution on ambiguous requests. Topics that could be misused (security, authentication, error handling, network tools) trigger over-caution even in legitimate professional contexts. The model lacks context to distinguish benign from harmful intent.

Fix

Option 1: Provide explicit role and context in system prompt

System prompt:
"You are a security engineering assistant for [Company Name]'s internal red team.
Users are credentialed security professionals conducting authorized penetration tests
and security research.

You SHOULD help with:
- CVE analysis and exploit research for defense purposes
- Security tool configuration (Burp Suite, nmap, Metasploit)
- Vulnerability assessment and threat modeling
- Code review for security flaws

You should NOT help with:
- Attacking systems without confirmed authorization
- Creating novel malware for offensive use

The users have verified authorization for their test environments. Assume good faith
for all security research questions."

Option 2: State authorization and context explicitly in the request

Instead of: "How do I bypass rate limiting?"

Use: "I'm building rate limiting for our API and need to understand bypass techniques
so I can test our implementation. What are common rate limit bypass patterns I should
test against?"

Instead of: "Write a script to crack passwords"

Use: "I'm implementing password strength validation. Write a script that tests common
weak password patterns so I can ensure our policy blocks them. Use rockyou.txt wordlist."

Option 3: Adjust refusal behavior for developer agents

System prompt:
"You are a senior software engineer assistant for a professional development team.

When evaluating whether to help with a request:
- Default to YES for technical questions, even if the topic could theoretically be misused
- Assume the user is a professional with legitimate purpose
- Do not add unsolicited safety warnings to standard technical code
- Do not refuse based on theoretical misuse scenarios when the request is clearly technical
- If a request is genuinely ambiguous, ask one clarifying question rather than refusing

You MAY add a brief note about security implications when directly relevant, but do not
refuse or extensively caveat standard engineering work."

Option 4: Decompose sensitive requests into components

# If a direct request triggers refusal, break it into neutral components

# Potentially refused:
"Write a script that tests if our login endpoint is vulnerable to timing attacks"

# Decomposed into neutral components:
step_1 = "Write a function that sends HTTP requests and measures response time in milliseconds"
step_2 = "Write a function that runs the same request N times and returns statistics"
step_3 = "Write a function that compares timing distributions between two request types"
step_4 = "Combine these into a CLI tool that takes an endpoint URL and username list"

Option 5: Detect over-refusal in your pipeline and re-route

REFUSAL_PATTERNS = [
    "I can't help with",
    "I'm unable to assist",
    "I won't be able to",
    "I don't feel comfortable",
    "This could be used to harm",
    "I must decline",
]

def is_refusal(response: str) -> bool:
    return any(pattern.lower() in response.lower() for pattern in REFUSAL_PATTERNS)

async def complete_with_refusal_recovery(prompt: str, context: str) -> str:
    response = await agent.complete(prompt)

    if is_refusal(response):
        # Add context and retry once
        contextualized_prompt = f"""Context: {context}

Given this context, please help with:
{prompt}

This is a legitimate professional request. Please provide direct technical assistance."""
        response = await agent.complete(contextualized_prompt)

    return response

# Usage
result = await complete_with_refusal_recovery(
    "How do I test for SQL injection in our login form?",
    context="I am a security engineer running authorized penetration tests on our own application."
)

Refusal vs. Legitimate Caution

Over-refusal (address this) Legitimate refusal (don’t circumvent)
Refusing to explain known CVEs Refusing to write zero-day exploits for unknown systems
Adding warnings to standard auth code Refusing to help attack systems without authorization
Refusing to write security tests Refusing to create malware targeting real infrastructure
Declining penetration testing help Refusing to help with social engineering attacks
Refusing to explain encryption algorithms Refusing to break encryption protecting others’ data

Expected Token Savings

Refusal + re-explanation + retry: ~4,000 tokens Clear context in system prompt prevents refusals: 0 wasted

Environment

  • Security research, penetration testing, and developer tooling contexts
  • Source: direct experience with professional security workflows

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