Individual skill
exploiting-ai-model-file-rce
Testing machine-learning model files and model-loading services for remote code execution caused by insecure deserialization (pickle/PyTorch), unsafe config instantiation (Hydra), archive path traversal, and dangerous layer types during authorized penetration tests of AI/ML pipelines.
internal/tools/skills/data/ai-security/exploiting-ai-model-file-rce/SKILL.md
Source commit d42f381ad34843e71a42658e5c57290c713e85af
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Network or broad shell
- Last checked
- Nov 9, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 1,331
- Repository last updated
- Nov 9, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- cybersecurity Repository topic
- security Repository topic
- bug-bounty Repository topic
- automation Repository topic
- autonomous-pentesting Repository topic
- ai-agent Repository topic
- ai-security Repository topic
- ethical-hacking Repository topic
- golang Repository topic
- penetration-testing Repository topic
- ai-security Declared skill tag
- model-deserialization Declared skill tag
- penetration-testing Declared skill tag
- security Derived category
- testing Derived category
- education Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
Read excerpt
# Exploiting AI Model File RCE
## When to Use
- During authorized assessments of ML training/inference pipelines, model registries, artifact buckets, or model hubs
- When a service downloads, loads, or "installs" models from user-controlled URLs or untrusted repositories
- When auto-resume/auto-deploy pipelines load checkpoints (`.ckpt`, `.pt`, `.pth`, `.bin`) without provenance checks
- When assessing web UIs like InvokeAI, TorchServe, Triton, or NeMo/HuggingFace coders that accept model files
- When reviewing whether "safe" formats (`.safetensors`, `.nemo`, repo `config.json`) still expose instantiation gadgets
## Prerequisites
- **Authorization**: Written penetration testing agreement covering the ML systems and any callback infrastructure
- **Python 3** with `torch`, `joblib`, `numpy`, `tensorflow`/`keras` to craft and load test artifacts in a sandbox