Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2026-40036 is a high-severity Data Amplification (CWE-409) vulnerability in Ryandfir Unfurl. Its CVSS base score is 8.7 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Network Denial of Service (T1498); ranked at the 41th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to AC-10 (Concurrent Session Control) and SC-6 (Resource Availability) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2026-40036 is an unbounded zlib decompression vulnerability in the parse_compressed.py component of Unfurl versions prior to 2026.04. This flaw allows remote attackers to trigger denial of service by processing maliciously crafted compressed data. It is associated with CWE-409 (Improper Handling of Highly Compressed Data) and CWE-770 (Allocation of Resources Without Limits or Throttling), earning a CVSS v3.1 base score of 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H).
Attackers can exploit the vulnerability remotely over the network with no authentication or user interaction required. By submitting highly compressed payloads via URL parameters to the /json/visjs endpoint, the decompression process expands the data to gigabytes in size, exhausting server memory and crashing the Unfurl service.
The vulnerability is fixed in Unfurl release v2026.04, available at https://github.com/obsidianforensics/unfurl/releases/tag/v2026.04. Further details on the issue and remediation are provided in the GitHub security advisory at https://github.com/obsidianforensics/unfurl/security/advisories/GHSA-h5qv-qjv4-pc5m and the VulnCheck advisory at https://www.vulncheck.com/advisories/dfir-unfurl-denial-of-service-via-unbounded-zlib-decompression.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-20779
Vulnerability Data
Unfurl before 2026.04 contains an unbounded zlib decompression vulnerability in parse_compressed.py that allows remote attackers to cause denial of service. Attackers can submit highly compressed payloads via URL parameters to the /json/visjs endpoint that expand to gigabytes, exhausting server memory…
more
and crashing the service.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 5 hardening rules · 3 OS baselines
V15.4.4
Mitigating Controls (NIST 800-53 r5) AI
Directly enforces a hard limit on concurrent sessions, structurally preventing unbounded resource allocation.
Requires explicit allocation of resources by priority or quota, directly stopping unlimited allocation.
Input validation can reject or limit decompression of data whose expansion ratio exceeds safe thresholds.
Imposes a limit on consecutive invalid attempts, preventing one specific class of unbounded resource consumption.
DoS protection limits the resource-exhaustion impact when a decompression bomb is processed.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Monitoring capacity and taking action to maintain availability directly reduces unchecked resource allocation.
Secure-development practices include input-validation and resource-limit checks that prevent improper handling of compressed data.
Runtime monitoring of compute resources can detect exhaustion caused by decompression bombs.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Baseline comparison of CPU, memory and bandwidth usage helps surface uncontrolled resource allocations before they cause service degradation.
Security testing can uncover decompression-bomb vulnerabilities before release.
Capacity projections and elasticity measures ensure that allocation requests are bounded and can be throttled, reducing the window in which an attacker can force unbounded resource reservations.
Defining retention periods and deletion schedules for backup copies prevents indefinite accumulation of data on storage media without corresponding resource-management controls.
Redundancy helps availability but does not address the root cause of the weakness.
Secure development lifecycle includes input validation and resource-limit checks that mitigate data-amplification attacks.
Hardening callouts derived
Configuration rules from DISA STIG baselines that bear on weaknesses of the type cited by this CVE. Each rule is shown with the relationship its mapping actually records, against the CWE it was authored against. Derived via CVE→CWE over `controls_xwalks` (authoritative rows only; rows rated `none` are excluded).
Oracle Linux 8 (2 rules)
- V-248552 OL 8 must be configured so that all network connections associated with SSH traffic terminate after becoming unresponsive. prevents CWE-770
- V-248553 OL 8 must be configured so that all network connections associated with SSH traffic are terminated after 10 minutes of becoming unresponsive. prevents CWE-770
Oracle Linux 9 (2 rules)
- V-271710 OL 9 must be configured so that all network connections associated with SSH traffic are terminated after 10 minutes of becoming unresponsive. prevents CWE-770
- V-271709 OL 9 must be configured so that all network connections associated with SSH traffic terminate after becoming unresponsive. prevents CWE-770
RHEL 8 (1 rule)
- V-230244 RHEL 8 must be configured so that all network connections associated with SSH traffic terminate after becoming unresponsive. prevents CWE-770