ctf-malware
Provides malware analysis and network traffic techniques for CTF challenges. Use when analyzing obfuscated scripts, malicious packages, custom crypto protocols, C2 traffic, PE/.NET binaries, RC4/AES encrypted communications, YARA rules, shellcode analysis, memory forensics for malware (Volatility malfind, process injection detection), anti-analysis techniques (VM/sandbox detection, timing evasion, API hashing, process injection, environment checks), or extracting malware configurations and indicators of compromise.
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Critical
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Security
4 findings: 2 critical severity, 2 high severity. Installing this skill is not recommended: please review these findings carefully if you do intend to do so.
E005: Suspicious download URL detected in skill instructions.
What this means
Detected a suspicious URL in the skill instructions that could lead the agent to download and execute malicious scripts or binaries. This includes links to executables from untrusted sources, typosquatting of official packages, URL shorteners that obscure the destination, and personal file hosting services.
Why it was flagged
These Telegram Bot API endpoints allow retrieval of arbitrary files when a bot token is available and are commonly abused by malware authors for exfiltration and hosting/pushing payloads, making them high-risk download sources in this context.
E006: Malicious code pattern detected in skill scripts.
What this means
Detected high-risk code patterns in the skill content — including its prompts, tool definitions, and resources — such as data exfiltration, backdoors, remote code execution, credential theft, system compromise, supply chain attacks, and obfuscation techniques.
Why it was flagged
The content contains explicit, actionable instructions and code for credential theft, C2/backdoor operations (RATs, remote command execution), process injection, ARP/MITM attacks, and data exfiltration—indicative of deliberate malicious behavior.
W007: Insecure credential handling detected in skill instructions.
What this means
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
Why it was flagged
The guide explicitly directs using a Telegram bot token extracted from malware to call getUpdates/getFile APIs, which requires the LLM to handle and embed the secret token verbatim in API requests.
W008: Secret detected in skill content (API keys, tokens, passwords).
What this means
Detected sensitive credentials directly embedded within the skill content, such as API keys, access tokens, private keys, or service-specific secrets. Secrets should never be hardcoded in plain text within skill instructions.
Why it was flagged
I looked for high-entropy literal values that could be used as real credentials. The only candidate that appears to be a non-placeholder, random-looking secret is the key source string in pe-and-dotnet.md used to derive an AES key; it is a complex literal (contains punctuation, mixed characters) and is used in key derivation code, so it looks like an actual hardcoded secret/key material. Other apparent "secrets" were ignored because they match the allowed false-positive patterns: - TOKEN = "bot_token_here" (placeholder) — documentation placeholder. - password = b"hardcoded_password" — descriptive/example low-entropy placeholder. - default passwords like "admin", "password", "p0ison" — known low-entropy defaults (setup/example). - "underling", "baal darksecret", "darksecret" in ARP/IRC examples — contextual CTF examples, simple words, not high-entropy usable credentials. - Any environment variable names, IPs, or alphabet strings are not credentials. Therefore I flag only the high-entropy literal in pe-and-dotnet.md as a potential leaked secret.
- Repository
- ljagiello/ctf-skills
- Commit
d19f35f
- Audited
- Security analysis
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