CVE-2025-61301: CAPEv2 Denial-of-Analysis Vulnerability

CVE-2025-61301 Overview

A denial-of-analysis vulnerability exists in CAPEv2, an open-source malware sandbox solution, specifically within the reporting/mongodb.py and reporting/jsondump.py modules. This vulnerability allows attackers who can submit samples to cause incomplete or missing behavioral analysis reports by generating deeply nested or oversized behavior data that trigger MongoDB BSON limits or orjson recursion errors when the sample executes in the sandbox.

Critical Impact

Attackers can submit specially crafted malware samples that evade full behavioral analysis by causing the reporting modules to fail, resulting in incomplete security intelligence and potential blind spots in threat detection.

Affected Products

• CAPEv2 (commit 52e4b43, on 2025-05-17)
• CAPEv2 installations utilizing MongoDB reporting
• CAPEv2 installations utilizing JSON dump reporting

Discovery Timeline

• 2025-10-20 - CVE-2025-61301 published to NVD
• 2026-04-15 - Last updated in NVD database

Technical Details for CVE-2025-61301

Vulnerability Analysis

This vulnerability is classified as a Resource Exhaustion issue (CWE-400: Uncontrolled Resource Consumption). The flaw resides in how CAPEv2 handles behavioral analysis data when processing malware samples that generate deeply nested object structures or oversized data outputs.

When a malicious sample executes within the CAPEv2 sandbox, it can deliberately produce behavioral data designed to exploit limitations in the underlying data serialization and storage mechanisms. Specifically, the vulnerability manifests when:

1. Behavioral data exceeds MongoDB's 16MB BSON document size limit
2. Deeply nested data structures trigger orjson's recursion depth limits during JSON serialization

The attack requires no authentication and can be executed remotely by any user with sample submission privileges. The vulnerability does not impact confidentiality or integrity but significantly affects the availability of analysis results.

Root Cause

The root cause stems from insufficient validation and handling of behavioral data size and nesting depth before attempting serialization and database storage operations. The reporting/mongodb.py and reporting/jsondump.py modules lack adequate safeguards to truncate, flatten, or otherwise process data that approaches or exceeds the technical limits of their underlying libraries (MongoDB BSON and orjson).

When malware generates behavioral artifacts specifically designed to exceed these thresholds, the reporting modules encounter unhandled exceptions, causing analysis reports to be incomplete or entirely missing from the final output.

Attack Vector

The attack vector is network-based and requires the attacker to have the ability to submit samples to the CAPEv2 instance. An attacker crafts a malicious sample that, when executed in the sandbox environment, generates deeply nested function calls, registry operations, or file system interactions that create excessively complex behavioral data structures.

The vulnerability can be exploited by designing malware that:

• Creates thousands of nested subprocess calls
• Performs recursive registry key operations generating deep hierarchies
• Generates circular reference patterns in behavioral telemetry

For detailed technical analysis and proof-of-concept code, refer to the GitHub PoC repository for CVE-2025-61301.

Detection Methods for CVE-2025-61301

Indicators of Compromise

• Analysis tasks completing without expected behavioral reports in MongoDB
• Error logs showing BSON document size exceeded exceptions in reporting/mongodb.py
• orjson recursion depth errors appearing in CAPEv2 processing logs
• Submitted samples with unusually high process creation or registry operation counts

Detection Strategies

• Monitor CAPEv2 logs for DocumentTooLarge exceptions from PyMongo
• Alert on orjson RecursionError exceptions in the reporting pipeline
• Compare expected report completeness against actual database entries
• Track samples that complete execution but lack corresponding analysis documents

Monitoring Recommendations

• Implement log aggregation and alerting for reporting module exceptions
• Configure dashboards to track report generation success rates over time
• Monitor MongoDB collection sizes and document insertion failure rates
• Set up automated integrity checks comparing submitted samples against completed analyses

How to Mitigate CVE-2025-61301

Immediate Actions Required

• Review CAPEv2 installation for affected commit version (52e4b43)
• Update to the latest CAPEv2 release from the official GitHub repository
• Audit existing analysis reports for completeness gaps
• Restrict sample submission access to trusted users until patched

Patch Information

Check the CAPEv2 GitHub repository for the latest security updates addressing this vulnerability. The CAPEv2 project homepage may also contain additional guidance on recommended versions.

Workarounds

• Implement pre-processing validation to reject samples that generate excessive behavioral data
• Configure MongoDB with custom document size handling to gracefully truncate oversized reports
• Add recursion depth limits at the application layer before invoking orjson serialization
• Deploy rate limiting on sample submissions from untrusted sources

# Example: Configure MongoDB to log oversized document attempts
# Add to mongod.conf for monitoring purposes
systemLog:
  verbosity: 1
  component:
    write:
      verbosity: 2

# Monitor for DocumentTooLarge errors
tail -f /var/log/mongodb/mongod.log | grep -i "documenttoolarge"