Comparison
plexiglass vs AI-Infra-Guard
Verdict
Pick plexiglass if plexiglass is a toolkit for detecting and mitigating vulnerabilities in Large Language Models through adversarial attacks and deep-learning techniques; pick AI-Infra-Guard if aI-Infra-Guard is designed for organizations looking to secure their AI infrastructures comprehensively through various scanning and evaluation tools.
Markdown twin · plexiglass alternatives · AI-Infra-Guard alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | plexiglass | AI-Infra-Guard |
|---|---|---|
| Maintenance | Slowing (178d since push) As of 3w · github_public_v1 | Very active (0d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) 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
- plexiglass
- A toolkit for detecting and protecting against vulnerabilities in Large Language Models (LLMs).
- AI-Infra-Guard
- A full-stack AI Red Teaming platform securing AI ecosystems
Stars
- plexiglass
- 153
- AI-Infra-Guard
- 4.3k
Forks
- plexiglass
- 18
- AI-Infra-Guard
- 419
Open issues
- plexiglass
- 0
- AI-Infra-Guard
- 13
Language
- plexiglass
- Python
- AI-Infra-Guard
- Python
Adopt for
- plexiglass
- Plexiglass is a toolkit for detecting and mitigating vulnerabilities in Large Language Models through adversarial attacks and deep-learning techniques.
- AI-Infra-Guard
- AI-Infra-Guard is designed for organizations looking to secure their AI infrastructures comprehensively through various scanning and evaluation tools.
Persona
- plexiglass
- -
- AI-Infra-Guard
- -
Runtime
- plexiglass
- -
- AI-Infra-Guard
- -
License
- plexiglass
- Apache-2.0
- AI-Infra-Guard
- Apache-2.0
Last pushed
- plexiglass
- Feb 4, 2026
- AI-Infra-Guard
- Jul 28, 2026
Categories
- plexiglass
- Evaluation & Observability
- AI-Infra-Guard
- Evaluation & Observability, LLM Frameworks
Trust and health
Maintenance
- plexiglass
- Slowing (36%)
- AI-Infra-Guard
- Very active (96%)
Days since push
- plexiglass
- 178d
- AI-Infra-Guard
- 0d
Open issues (now)
- plexiglass
- 0
- AI-Infra-Guard
- 13
Full report
- plexiglass
- Trust report
- AI-Infra-Guard
- Trust report
Shared compatibility
- Python · plexiglass: Python runtime · AI-Infra-Guard: Python runtime
Choose plexiglass if…
- Tags unique to plexiglass: adversarial-attacks, adversarial-machine-learning, cybersecurity, deep-learning.
- When a team needs to evaluate the robustness of their LLM against specific adversarial attack vectors within Python-based projects.
- Leaner open-issue backlog (0).
When NOT to use plexiglass
- If a project is not using Python, because Plexiglass is specifically built for Python environments.
- When the team does not have access to the deep-learning techniques required by Plexiglass, as it heavily relies on such methods to mitigate vulnerabilities.
Choose AI-Infra-Guard if…
- Tags unique to AI-Infra-Guard: agent-security, ai-red-teaming, llm-evaluation, security-tools.
- Also covers LLM Frameworks.
- AI-Infra-Guard ships Docker support for self-hosted deployment.
- If you need advanced LLM jailbreak evaluation capabilities specific to the vulnerabilities identified by Tencent's research, consider using AI-Infra-Guard.
When NOT to use AI-Infra-Guard
- Avoid if you are looking exclusively for a tool that focuses solely on the runtime behavior of LLMs without broader infrastructural scanning capabilities.
- Not recommended when your primary focus is on network-level security rather than comprehensive AI infrastructure security assessments and evaluations.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (safellama/plexiglass) · observed Aug 2, 2026
- GitHub forks (safellama/plexiglass) · observed Aug 2, 2026
- Last push (safellama/plexiglass) · observed Feb 4, 2026
- License file (Apache-2.0) · observed Aug 2, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Tencent/AI-Infra-Guard) · observed Jul 28, 2026
- GitHub forks (Tencent/AI-Infra-Guard) · observed Jul 28, 2026
- Last push (Tencent/AI-Infra-Guard) · observed Jul 28, 2026
- License file (Apache-2.0) · observed Jul 28, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: plexiglass 153 · AI-Infra-Guard 4.3k (synced Aug 2, 2026).
Common questions
- What is the difference between plexiglass and AI-Infra-Guard?
- plexiglass: A toolkit for detecting and protecting against vulnerabilities in Large Language Models (LLMs).. AI-Infra-Guard: A full-stack AI Red Teaming platform securing AI ecosystems. See the comparison table for live GitHub stats and shared categories.
- When should I choose plexiglass over AI-Infra-Guard?
- Choose plexiglass over AI-Infra-Guard when Tags unique to plexiglass: adversarial-attacks, adversarial-machine-learning, cybersecurity, deep-learning; When a team needs to evaluate the robustness of their LLM against specific adversarial attack vectors within Python-based projects; Leaner open-issue backlog (0).
- When should I choose AI-Infra-Guard over plexiglass?
- Choose AI-Infra-Guard over plexiglass when Tags unique to AI-Infra-Guard: agent-security, ai-red-teaming, llm-evaluation, security-tools; Also covers LLM Frameworks; AI-Infra-Guard ships Docker support for self-hosted deployment; If you need advanced LLM jailbreak evaluation capabilities specific to the vulnerabilities identified by Tencent's research, consider using AI-Infra-Guard.
- When should I avoid plexiglass?
- If a project is not using Python, because Plexiglass is specifically built for Python environments. When the team does not have access to the deep-learning techniques required by Plexiglass, as it heavily relies on such methods to mitigate vulnerabilities.
- When should I avoid AI-Infra-Guard?
- Avoid if you are looking exclusively for a tool that focuses solely on the runtime behavior of LLMs without broader infrastructural scanning capabilities. Not recommended when your primary focus is on network-level security rather than comprehensive AI infrastructure security assessments and evaluations.
- Is plexiglass or AI-Infra-Guard more popular on GitHub?
- AI-Infra-Guard has more GitHub stars (4,316 vs 153). Stars measure visibility, not whether either tool fits your constraints.
- Are plexiglass and AI-Infra-Guard open source?
- Yes - both are open-source projects on GitHub (plexiglass: Apache-2.0, AI-Infra-Guard: Apache-2.0).
- Where can I find alternatives to plexiglass or AI-Infra-Guard?
- GraphCanon lists graph-backed alternatives at plexiglass alternatives and AI-Infra-Guard alternatives (plexiglass markdown twin, AI-Infra-Guard 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, plexiglass or AI-Infra-Guard?
- plexiglass: Slowing. AI-Infra-Guard: Very active. 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 plexiglass and AI-Infra-Guard?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: plexiglass trust report; AI-Infra-Guard trust report.