Mythos Finds a Curl Vulnerability

Role and impact of Mythos on curl

• Many note that curl had already been heavily scanned with other AI tools, fuzzers, and audits; expectations of a “tsunami” of new bugs from Mythos were therefore unrealistic.
• Mythos reportedly found five plausible issues, of which one will become a low‑severity CVE. Commenters see this as evidence it’s an incremental improvement, not a revolution.
• Some argue the result mainly reflects curl’s unusually high security maturity; others counter that curl still gets new CVEs regularly, so a truly game‑changing tool should find more.

Comparison with other AI tools and workflows

• Previous AI-based tools (AISLE, ZeroPath, Codex Security, etc.) have already led to hundreds of bugfixes and around a dozen CVEs in curl.
• Several suggest Mythos looks like “Opus plus a harness/prompt,” with the real gains coming from good pipelines, adversarial review, and dynamic validation rather than the raw model.
• Others say even current public models can already find bugs and generate PoC exploits in large codebases; Mythos mostly lowers the skill required.

Firefox / broader ecosystem vs curl

• Firefox’s use of Mythos reportedly surfaced hundreds of vulnerabilities, far more than earlier experiments with prior models. Some view this as strong evidence of a step change.
• Skeptics note differences in harness maturity, scope of scanning, and token budgets; they argue you can’t directly compare Firefox “first-time large-scale AI scan” numbers with curl’s “post-many-AI-passes” state.
• Unclear: exact false-positive rates and how much of Firefox’s haul truly required Mythos versus any strong model plus a good pipeline.

Danger, accessibility, and attacker economics

• One camp stresses that Mythos (and similar models) make high‑end vulnerability discovery and exploitation accessible to non-experts, which meaningfully changes attacker economics.
• Others argue this capability already existed with prior models; Mythos primarily makes it easier for people who “don’t know what they’re doing.”
• There’s concern that defenders are now racing against automated scanning of vast software ecosystems, particularly for medium/low‑scrutiny projects.

Marketing, hype, and co‑marketing concerns

• Many see Mythos framing (“too powerful to release,” “reshaping cybersecurity”) as aggressive marketing, likened to earlier “too dangerous to release” claims about past models.
• Some suspect co‑marketing arrangements with browser vendors and governments, or at least mutually beneficial publicity.
• Others push back, saying the capabilities are real, and that using vivid language to get C‑suites to fund security work is pragmatically helpful, even if dramatized.