awesome-llm-security
A curation of tools, documents and projects about LLM Security
GraphCanon updated Oct 11, 2026 · GitHub synced Oct 11, 2026
156views this month
Decision brief
Awesome LLM Security is a curated list of resources related to the security aspects of large language models. It covers various attack methodologies, defenses, and platform security through papers, benchmarks, tools, and
Good fit when
- When you are specifically looking for detailed information on both white-box and black-box attacks targeted at Large Language Models (LLMs), which 'awesome-llm-security' comprehensively catalogs.
- If you need resources that focus heavily on multi-modal adversarial techniques against LLMs, including visual and sound-based indirect instruction injections, as provided in the repository's list.
Avoid when
- When your primary interest is in general software security or vulnerabilities unrelated to language models, since 'awesome-llm-security' zeroes in on attack vectors specifically for LLMs.
- If you are solely interested in tools and methods that are not publicly discussed or peer-reviewed; the repository focuses on documented approaches within reputable academic publications.
- Hosting:
- unknown
- Pricing:
- freemium - As an open-source project without defined pricing models, its use is generally free under the terms of its license (license details are not provided).
Observed Jul 11, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Dormant (417d since push)
- As of Oct 11, 2026
- Provenance
- Not a fork · Organization account
- As of Oct 11, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/corca-ai/awesome-llm-securitySimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Curates resources related to security aspects of large language models including attack methodologies, defenses, and platform security.
Capability facts
No sourced capability facts yet. Facts appear after ingest scans repo manifests (Dockerfile, package.json, MCP configs).
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Oct 11, 2026)
- "Multi-step Jailbreaking Privacy Attacks on ChatGPT", 2023-04, EMNLP 23, `privacy`, [[paper]](https://www.themoonlight.io/paper/shaSource link
Tags
README
Awesome LLM Security A curation of awesome tools, documents and projects about LLM Security. Contributions are always welcome. Please read the Contribution Guidelines before contributing. [!NOTE] ⚡ For efficient research navigation, we’re sharing PDFs via Moonlight, which provide...
For agents
This page has a .md twin and JSON over the API.