Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add meltedinhex/analyst-ai-pack --skill identifying-anti-debugging-techniquesgit clone --depth 1 https://github.com/meltedinhex/analyst-ai-packWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/identifying-anti-debugging-techniques)<a href="https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/identifying-anti-debugging-techniques"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/identifying-anti-debugging-techniques.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00072 | $0.00825 |
| Opus 5 | $0.00036 | $0.00413 |
| Sonnet 5 | $0.00014 | $0.00165 |
| Haiku 4.5 | $0.00007 | $0.00082 |
Grade A, and why
identifying-anti-debugging-techniques scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Identifying Anti-Debugging Techniques
When to Use
- A sample behaves differently (or exits) under a debugger and you need to find the checks.
- You are stuck at a point where execution diverges when analysis tooling is present.
- You want to neutralize anti-debug logic to continue dynamic analysis.
Do not use brute removal of every check — some are tied to control flow or decryption keys; faking the expected result is usually safer than deleting the check.
Prerequisites
- x64dbg (with anti-debug plugins like ScyllaHide) inside the victim VM.
- A disassembler to locate checks statically.
- Familiarity with the Windows PEB and debug APIs.
Workflow
Step 1: Enumerate likely checks statically
Scan imports and code for common anti-debug primitives:
python scripts/analyst.py scan sample.bin
API-based : IsDebuggerPresent, CheckRemoteDebuggerPresent, NtQueryInformationProcess
PEB-based : BeingDebugged (PEB+0x2), NtGlobalFlag (PEB+0xBC/0x68)
Timing : rdtsc, GetTickCount/QueryPerformanceCounter deltas around code
Exceptions : INT3/INT2D, SetUnhandledExceptionFilter, single-step traps
Self-checks : CRC of own code, breakpoint (0xCC) scanning
Step 2: Confirm at runtime
Set breakpoints on the detection APIs and observe how the result is used (a conditional jump that leads to exit vs. real code).
Step 3: Neutralize
Prefer faking results over deletion: force IsDebuggerPresent to return 0, clear the PEB
BeingDebugged flag, or use ScyllaHide to hook the common checks automatically. For timing,
patch the comparison or reduce measured deltas.
Step 4: Re-run and continue
With checks neutralized, proceed to unpacking/behavior analysis. Re-scan in case later stages add more checks.
Validation
- After neutralization, execution follows the same path as on a non-debugged run.
- Faked check results do not break decryption or control flow (no corrupted code paths).
- The sample reaches and reveals its real behavior.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 99 lines · 72 tokens per session scan A 3ac8a9db5b69
identifying-anti-debugging-techniques is a skill published in the GitHub repository meltedinhex/analyst-ai-pack (22 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 72 tokens to every session and 825 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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