AI Found Twelve New Vulnerabilities in OpenSSL
Vulnerabilities mentionedAll →
| CVE | Vulnerability | CVSS | EPSS | Flags | Affected | Exposure | Published |
|---|---|---|---|---|---|---|---|
| CVE-2025-15467 | Stack Buffer Overflow in OpenSSL 3.x CMS AEAD Parsing Enables DoS/RCE OpenSSL 3.0, 3.3, 3.4, 3.5 and 3.6 contain a stack-based out-of-bounds write (CWE-787/CWE-120) in their CMS parser: when decoding CMS AuthEnvelopedData or EnvelopedData parameters for AEAD ciphers such as AES-GCM, the ASN.1-encoded IV is copied into a fixed-size stack buffer without checking its length. An attacker triggers it by sending a crafted CMS/PKCS#7 message (e.g., an S/MIME enveloped message) with an oversized IV to any application that parses it; the overflow occurs before authentication or tag verification, so no valid key material is required, though the target must process attacker-supplied content (CVSS UI:R). Successful exploitation causes a crash (denial of service) and, depending on platform and toolchain mitigations, potentially remote code execution. Only applications and services parsing untrusted CMS content with the listed OpenSSL 3.x series are affected; OpenSSL 1.1.1, 1.0.2 and the FIPS modules in 3.0/3.3/3.4/3.5/3.6 are not affected, since the CMS implementation lies outside the FIPS module boundary. There is no confirmed in-the-wild exploitation or KEV listing yet, but a public proof-of-concept exists and EPSS assigns a 48.2% (99th-percentile) probability of exploitation within 30 days. Do: Upgrade all OpenSSL 3.0/3.3/3.4/3.5/3.6 deployments to the patched releases referenced in the OpenSSL security advisory, and rebuild or update products, distributions and appliances that bundle affected 3.x libraries. Until patched, mitigate by avoiding or restricting parsing of untrusted CMS/PKCS#7 (Auth)EnvelopedData with AEAD ciphers (e.g., disable or filter S/MIME enveloped-mail processing for external senders) and inventory which services accept CMS content. Note that FIPS-module-only deployments are unaffected because CMS parsing is outside the module boundary. | 8.8 | 48% | PoC |
| masstens of millions of installations run OpenSSL 3.x, though practical exposure is limited to applications parsing untrusted CMS/AEAD content |
Full article325 words · extracted from schneier.com · click to collapse
The title of the post is”What AI Security Research Looks Like When It Works,” and I agree:
In the latest OpenSSL security release> on January 27, 2026, twelve new zero-day vulnerabilities (meaning unknown to the maintainers at time of disclosure) were announced. Our AI system is responsible for the original discovery of all twelve, each found and responsibly disclosed to the OpenSSL team during the fall and winter of 2025. Of those, 10 were assigned CVE-2025 identifiers and 2 received CVE-2026 identifiers. Adding the 10 to the three we already found in the Fall 2025 release, AISLE is credited for surfacing 13 of 14 OpenSSL CVEs assigned in 2025, and 15 total across both releases. This is a historically unusual concentration for any single research team, let alone an AI-driven one.
These weren’t trivial findings either. They included CVE-2025-15467, a stack buffer overflow in CMS message parsing that’s potentially remotely exploitable without valid key material, and exploits for which have been quickly developed online. OpenSSL rated it HIGH severity; NIST‘s CVSS v3 score is 9.8 out of 10 (CRITICAL, an extremely rare severity rating for such projects). Three of the bugs had been present since 1998-2000, for over a quarter century having been missed by intense machine and human effort alike. One predated OpenSSL itself, inherited from Eric Young’s original SSLeay implementation in the 1990s. All of this in a codebase that has been fuzzed for millions of CPU-hours and audited extensively for over two decades by teams including Google’s.
In five of the twelve cases, our AI system directly proposed the patches that were accepted into the official release.
AI vulnerability finding is changing cybersecurity, faster than expected. This capability will be used by both offense and defense.
More.
Tags: AI, patching, SSL, vulnerabilities, zero-day
Sidebar photo of Bruce Schneier by Joe MacInnis.
Text extracted automatically; images, tables and formatting may be missing. Original: https://www.schneier.com/blog/archives/2026/02/ai-found-twelve-new-vulnerabilities-in-openssl.html