Comparison
PromptAttack vs AutoDefense
Verdict
Pick PromptAttack if promptAttack is an LLM-targeted adversarial attack tool that leverages prompt engineering to generate adversarial samples keeping semantic intact but misclassifying outputs; pick AutoDefense if autoDefense uses a multi-agent framework to mitigate jailbreak attacks on LLMs, installed via Python.
Markdown twin · PromptAttack alternatives · AutoDefense alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | PromptAttack | AutoDefense |
|---|---|---|
| Maintenance | Dormant (560d since push) As of 2w · github_public_v1 | Slowing (201d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2w · github_public_v1 | Not a fork · Personal account As of 2w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- PromptAttack
- An LLM can Fool Itself: A Prompt-Based Adversarial Attack
- AutoDefense
- Multi-Agent LLM Defense against Jailbreak Attacks
Stars
- PromptAttack
- 117
- AutoDefense
- 68
Forks
- PromptAttack
- 17
- AutoDefense
- 20
Open issues
- PromptAttack
- 0
- AutoDefense
- 1
Language
- PromptAttack
- Python
- AutoDefense
- Python
Adopt for
- PromptAttack
- PromptAttack is an LLM-targeted adversarial attack tool that leverages prompt engineering to generate adversarial samples keeping semantic intact but misclassifying outputs.
- AutoDefense
- AutoDefense uses a multi-agent framework to mitigate jailbreak attacks on LLMs, installed via Python.
Persona
- PromptAttack
- -
- AutoDefense
- -
Runtime
- PromptAttack
- -
- AutoDefense
- -
License
- PromptAttack
- -
- AutoDefense
- MIT
Last pushed
- PromptAttack
- Jan 21, 2025
- AutoDefense
- Jan 15, 2026
Categories
- PromptAttack
- Evaluation & Observability
- AutoDefense
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- PromptAttack
- Dormant (18%)
- AutoDefense
- Slowing (36%)
Days since push
- PromptAttack
- 560d
- AutoDefense
- 201d
Open issues (now)
- PromptAttack
- 0
- AutoDefense
- 1
OSV dependency advisories
- PromptAttack
- Published findings
- AutoDefense
- No lockfile (source not queried)
Full report
- PromptAttack
- Trust report
- AutoDefense
- Trust report
Shared compatibility
- Python · PromptAttack: Python runtime · AutoDefense: Python runtime
Choose PromptAttack if…
- Tags unique to PromptAttack: adversarial attack, language model evaluation, prompt-engineering.
- For targeted analysis of adversarial robustness in specific language models.
- More GitHub stars (117 vs 68) - visibility, not fit.
When NOT to use PromptAttack
- If the focus is on general model improvement rather than adversarial testing.
- When working with proprietary or sensitive data that cannot be manipulated via external prompt tools, given potential data leakage concerns.
Choose AutoDefense if…
- Tags unique to AutoDefense: defense-mechanism, jailbreak prevention, large language models, llm-defense.
- Also covers AI Agents.
- Implementing robust defenses for enterprise-level AI projects with high-security requirements
When NOT to use AutoDefense
- Projects requiring light-weight solutions where multi-agent systems might introduce complexity overhead
- Environments without access to Python and its ecosystem, as AutoDefense depends on specific Python packages
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (GodXuxilie/PromptAttack) · observed Aug 5, 2026
- GitHub forks (GodXuxilie/PromptAttack) · observed Aug 5, 2026
- Last push (GodXuxilie/PromptAttack) · observed Jan 21, 2025
- License file (unknown) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (XHMY/AutoDefense) · observed Aug 5, 2026
- GitHub forks (XHMY/AutoDefense) · observed Aug 5, 2026
- Last push (XHMY/AutoDefense) · observed Jan 15, 2026
- License file (MIT) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: PromptAttack 117 · AutoDefense 68 (synced Aug 5, 2026).
Common questions
- What is the difference between PromptAttack and AutoDefense?
- PromptAttack: An LLM can Fool Itself: A Prompt-Based Adversarial Attack. AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks. See the comparison table for live GitHub stats and shared categories.
- When should I choose PromptAttack over AutoDefense?
- Choose PromptAttack over AutoDefense when Tags unique to PromptAttack: adversarial attack, language model evaluation, prompt-engineering; For targeted analysis of adversarial robustness in specific language models; More GitHub stars (117 vs 68) - visibility, not fit.
- When should I choose AutoDefense over PromptAttack?
- Choose AutoDefense over PromptAttack when Tags unique to AutoDefense: defense-mechanism, jailbreak prevention, large language models, llm-defense; Also covers AI Agents; Implementing robust defenses for enterprise-level AI projects with high-security requirements.
- When should I avoid PromptAttack?
- If the focus is on general model improvement rather than adversarial testing. When working with proprietary or sensitive data that cannot be manipulated via external prompt tools, given potential data leakage concerns.
- When should I avoid AutoDefense?
- Projects requiring light-weight solutions where multi-agent systems might introduce complexity overhead Environments without access to Python and its ecosystem, as AutoDefense depends on specific Python packages
- Is PromptAttack or AutoDefense more popular on GitHub?
- PromptAttack has more GitHub stars (117 vs 68). Stars measure visibility, not whether either tool fits your constraints.
- Are PromptAttack and AutoDefense open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to PromptAttack or AutoDefense?
- GraphCanon lists graph-backed alternatives at PromptAttack alternatives and AutoDefense alternatives (PromptAttack markdown twin, AutoDefense markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, PromptAttack or AutoDefense?
- PromptAttack: Dormant. AutoDefense: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for PromptAttack and AutoDefense?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: PromptAttack trust report; AutoDefense trust report.