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Comparison

ALERT vs weak-to-strong

Verdict

Pick ALERT if aLERT is designed specifically for red-teaming based safety evaluation on large language models, using MIT licensed prompts and adversarial augmentation; pick weak-to-strong if weak-to-Strong is an inference-time attack exploiting smaller models to guide larger LLMs towards harmful output generation.

Markdown twin · ALERT alternatives · weak-to-strong alternatives

GraphCanon updated 2w

ALERT logo

ALERT

Babelscape/ALERT

★ 59pushed Sep 20, 2024
vs
weak-to-strong logo

weak-to-strong

XuandongZhao/weak-to-strong

★ 90pushed May 2, 2025

Trust & integrity

SignalALERTweak-to-strong
Maintenance
Dormant (687d since push)
As of 2w · github_public_v1
Dormant (459d since push)
As of 3w · github_public_v1
Provenance
Not a fork · Organization account
As of 2w · github_public_v1
Not a fork · Personal account
As of 3w · github_public_v1
OSV dependency advisories
No published findings from this source as of 2026-07-15
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
ALERT trust reportweak-to-strong trust reportTrust methodology

Tagline

ALERT
A Comprehensive Benchmark for Assessing Large Language Models' Safety Through Red Teaming
weak-to-strong
Novel Inference-Time Attack Leveraging Small Models to Guide Larger LLMs into Generating Harmful Outputs

Stars

ALERT
59
weak-to-strong
90

Forks

ALERT
8
weak-to-strong
10

Open issues

ALERT
0
weak-to-strong
3

Language

ALERT
Python
weak-to-strong
Python

Adopt for

ALERT
ALERT is designed specifically for red-teaming based safety evaluation on large language models, using MIT licensed prompts and adversarial augmentation.
weak-to-strong
Weak-to-Strong is an inference-time attack exploiting smaller models to guide larger LLMs towards harmful output generation.

Persona

ALERT
-
weak-to-strong
-

Runtime

ALERT
-
weak-to-strong
-

License

ALERT
Other
weak-to-strong
MIT

Last pushed

ALERT
Sep 20, 2024
weak-to-strong
May 2, 2025

Categories

ALERT
Evaluation & Observability
weak-to-strong
Inference & Serving

Trust and health

Days since push

ALERT
687d
weak-to-strong
459d

Open issues (now)

ALERT
0
weak-to-strong
3

Owner type

ALERT
Organization
weak-to-strong
User

OSV dependency advisories

ALERT
No published findings from this source as of 2026-07-15
weak-to-strong
No lockfile (source not queried)

Full report

ALERT
Trust report
weak-to-strong
Trust report

Choose ALERT if…

  • License: ALERT is Other, weak-to-strong is MIT.
  • Tags unique to ALERT: ai, artificial-intelligence, benchmark, bias-detection.
  • Also covers Evaluation & Observability.
  • When evaluating safety metrics of large language models through red-teaming approaches

When NOT to use ALERT

  • If your evaluation does not require bias detection or safety assessment under adversarial conditions
  • In scenarios where a broader range of model aspects beyond safety is needed, as ALERT focuses primarily on safety benchmarks
GitHubDetails

Choose weak-to-strong if…

  • License: weak-to-strong is MIT, ALERT is Other.
  • Requirements: Min 8 GB RAM; The smaller models guiding the large LLM must be available.; A high-performance computing environment might be necessary if running on very large datasets or models..
  • Tags unique to weak-to-strong: inference-time attack, jailbreaking, large language models.
  • Also covers Inference & Serving.
  • Use it for research purposes specifically geared at understanding the vulnerabilities in large language models and improving their robustness against adversarial attacks.

When NOT to use weak-to-strong

  • Do not use it for applications requiring ethical guidelines adherence as it is designed to navigate around the safety mechanisms in large language models.
  • Avoid using this tool if you are developing systems that must ensure consistent alignment and prevent any form of harmful output generation, such as public communication platforms or education tools.
GitHubDetails

Explore

ALERT trust report →weak-to-strong trust report →Evaluation & Observability category →Inference & Serving category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: ALERT 59 · weak-to-strong 90 (synced Aug 9, 2026).

Common questions

What is the difference between ALERT and weak-to-strong?
ALERT: A Comprehensive Benchmark for Assessing Large Language Models' Safety Through Red Teaming. weak-to-strong: Novel Inference-Time Attack Leveraging Small Models to Guide Larger LLMs into Generating Harmful Outputs. See the comparison table for live GitHub stats and shared categories.
When should I choose ALERT over weak-to-strong?
Choose ALERT over weak-to-strong when License: ALERT is Other, weak-to-strong is MIT; Tags unique to ALERT: ai, artificial-intelligence, benchmark, bias-detection; Also covers Evaluation & Observability; When evaluating safety metrics of large language models through red-teaming approaches.
When should I choose weak-to-strong over ALERT?
Choose weak-to-strong over ALERT when License: weak-to-strong is MIT, ALERT is Other; Requirements: Min 8 GB RAM; The smaller models guiding the large LLM must be available.; A high-performance computing environment might be necessary if running on very large datasets or models.; Tags unique to weak-to-strong: inference-time attack, jailbreaking, large language models; Also covers Inference & Serving; Use it for research purposes specifically geared at understanding the vulnerabilities in large language models and improving their robustness against adversarial attacks.
When should I avoid ALERT?
If your evaluation does not require bias detection or safety assessment under adversarial conditions In scenarios where a broader range of model aspects beyond safety is needed, as ALERT focuses primarily on safety benchmarks
When should I avoid weak-to-strong?
Do not use it for applications requiring ethical guidelines adherence as it is designed to navigate around the safety mechanisms in large language models. Avoid using this tool if you are developing systems that must ensure consistent alignment and prevent any form of harmful output generation, such as public communication platforms or education tools.
Is ALERT or weak-to-strong more popular on GitHub?
weak-to-strong has more GitHub stars (90 vs 59). Stars measure visibility, not whether either tool fits your constraints.
Are ALERT and weak-to-strong open source?
Yes - both are open-source projects on GitHub (ALERT: Other, weak-to-strong: MIT).
Where can I find alternatives to ALERT or weak-to-strong?
GraphCanon lists graph-backed alternatives at ALERT alternatives and weak-to-strong alternatives (ALERT markdown twin, weak-to-strong 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, ALERT or weak-to-strong?
ALERT: Dormant. weak-to-strong: Dormant. 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 ALERT and weak-to-strong?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ALERT trust report; weak-to-strong trust report.

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