Open Babel has out-of-bounds write in MOPAC translationVectors[] (UNIT CELL TRANSLATION)

### Summary A memory-safety vulnerability in Open Babel's MOPAC output parser allowed an out-of-bounds write into the `translationVectors[]` array when reading the "UNIT CELL TRANSLATION" block of a crafted input file. ### Details The MOPAC output reader stored translation vectors from the UNIT CELL TRANSLATION block into a fixed-size `translationV...

📋 Executive Summary

🧮 Severity Anatomy — CVSS 3.1 vector, decoded from the primary record

The base score summarizes severity in one number; the vector explains why. Each row below is a direct read of the official CVSS vector — verifiable against the NVD record.

🧬 Weakness Anatomy — CWE-119, the underlying flaw class

This vulnerability is classified as CWE-119: Improper Restriction of Memory Buffer in the primary record. The mechanics below are characteristic of this weakness class (per the MITRE CWE corpus), not a claim about a specific exploit observed against your environment.

⚠️ Business Impact Analysis

• ⚠️ pip openbabel users face material security risk requiring immediate remediation

🔗 Representative Attack Path

A typical attack path for this vulnerability class, mapped to MITRE ATT&CK. This is a representative model to guide detection and defense — not a claim of observed activity against a specific target. Confirm specifics against the primary sources below.

⚠ Deep Dive Analysis

This high-severity vulnerability in pip openbabel (CVSS 7.8) represents a significant attack surface. SENTINEL APEX assesses exploitation to be technically feasible with moderate effort. Organizations running openbabel in internet-facing or privileged positions face immediate risk.

SENTINEL APEX URGENCY: ELEVATED. Score: 44/100 LOW. Patch before exploitation activity begins.

🧠 Structured Intelligence Assessment

SENTINEL APEX analytical tradecraft separates verified fact from labeled assessment and states intelligence gaps explicitly. Confidence reflects evidentiary support, not certainty.

✔ Verified Facts

• Affected CVE(s): CVE-2022-46292, CVE-2022-46292.
• Affected technology: pip openbabel.
• CVSS base score of 7.8 assigned by an authoritative source.

🧩 Analyst Assessments

• MEDIUM CONF Technical severity is assessed as high (CVSS 7.8); realized business impact depends on asset exposure and data classification.

❓ Intelligence Gaps

• No confirmed public IOCs are available at report time; detection currently relies on behavioral analytics.
• In-the-wild exploitation is unconfirmed as of this report.
• Attribution to a specific threat actor is not established by the available evidence.
• The source lacks sufficient technical detail for confident MITRE ATT&CK mapping.

🔮 Forward Outlook

• LOW CONF Exploitation activity may emerge as technical details become public; monitor vendor advisories.

🎯 MITRE ATT&CK Mapping

🔴 CVE Reference

🔍 Detection Rules — Sigma (SIEM)

Deploy to Splunk, Elastic, Microsoft Sentinel, or QRadar. SOC Pro subscribers receive pre-compiled SIEM-native query packs updated with each pipeline run.

📡 Detection Rules — YARA (Endpoint)

Deploy to endpoint detection platforms. Enterprise subscribers receive tuned, FP-validated YARA rule packs.

🎯 Multi-Audience Intelligence Products

This single analysis is packaged for every stakeholder — from the boardroom to the SOC — plus a machine-readable feed for API and MSSP integration. Enterprise & SOC Pro subscribers receive these as structured deliverables.

🏛 Executive Advisory — CISO / Security Leadership

• Affected CVE(s): CVE-2022-46292, CVE-2022-46292.
• Affected technology: pip openbabel.
• CVSS base score of 7.8 assigned by an authoritative source.

📋 Board Brief

• A high-severity cyber threat affects pip openbabel.
• Technical severity is rated 7.8/10.
• Primary exposure is operational disruption, data loss, and potential regulatory liability (e.g. GDPR, NIS2, DORA, SOC 2) where in-scope systems are affected.
• Mitigation depends on vendor guidance and compensating controls.
• Recommended posture: authorize prioritized remediation and confirm detection coverage with the security team.

🛡 SOC Bulletin

Severity HIGH · Detection coverage: 0 technique(s) across behavioral analytics · 0 network rule(s)

• P1: Sweep 14 days of telemetry for the mapped ATT&CK techniques.
• P2: Update threat-intel platform and downstream detection feeds with confirmed indicators.

🛡️ SOC Response Playbook

• 1IMMEDIATE (0-1hr): Identify all instances of openbabel in your environment via CMDB/asset inventory
• 2IMMEDIATE (0-1hr): Apply vendor patch — no maintenance window exception for LOW threats
• 3IMMEDIATE (1-2hr): If no patch available: implement WAF rules, ACLs, or network-level compensating controls
• 4SHORT-TERM (2-4hr): Deploy Sigma detection rule to SIEM — validate alert generation in test environment
• 5SHORT-TERM (4-8hr): Review logs for exploitation indicators (anomalous openbabel requests, error spikes)
• 6SHORT-TERM (8-24hr): Hunt for post-exploitation: new admin accounts, scheduled tasks, lateral movement
• 7MONITOR: Subscribe to pip security advisories for patch updates
• 8ONGOING: Track SENTINEL APEX intelligence feed for follow-on campaigns targeting openbabel

📎 Intelligence References

• github.com/advisories/GHSA-55f6-pf8r-c2f4
• github.com/openbabel/openbabel/security/advisories/GHSA-55f6-pf8r-c2f4
• nvd.nist.gov/vuln/detail/CVE-2022-46292
• github.com/openbabel/openbabel/commit/40e852138f21d586b7ccdce6329e7b23
• talosintelligence.com/vulnerability_reports/TALOS-2022-1666
• 📌 NVD — CVE-2022-46292