Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessAccess public agent interface
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DeliveryCraft prompt triggering web_fetch/web_search
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ExploitAgent requests internal URL (metadata/admin endpoint)
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ExecutionServer executes SSRF from trusted network position
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PersistExtract credentials/data from response
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ImpactPivot to compromised infrastructure
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A01:2025 - Broken Access Control
ASVS 5.0
V4 - API and Web Service URL allowlisting, SSRF prevention
MITRE ATT&CK
2 techniques across 2 tactics: Initial Access, Credential Access The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Exploitation Conditions | Exploitation requires the target OpenHarness deployment to expose AI agent sessions with enabled web_fetch or web_search tools via a network-accessible interface (web application, API, chatbot). Attacker must influence agent behavior through natural language prompts or API calls to trigger tool invocation with malicious URL parameters-no authentication required (PR:N) and no user interaction needed (UI:N) beyond normal interaction with the agent service. Successful exploitation depends on what internal HTTP services are network-reachable from the victim host: cloud environments with metadata endpoints at 169.254.169.254, internal admin panels on localhost ports, private network services in RFC1918 ranges, or Kubernetes service endpoints yield highest impact. Deployments isolated from sensitive internal networks or those running in restricted network namespaces without access to cloud metadata services face reduced risk. The Changed scope (S:C) confirms exploitation transcends the vulnerable application's own authorization boundary to access separate resources. |
| Impact | CVSS 8.3 (High) reflects the network attack vector (AV:N), no authentication required (PR:N), and changed scope (S:C) - accurate for SSRF enabling internal network reconnaissance and data exfiltration. The Low confidentiality/integrity/availability ratings (C:L/I:L/A:L) understate real-world impact: successful SSRF against cloud metadata services yields IAM credentials (high confidentiality), and requests to administrative endpoints can modify configurations (high integrity). EPSS score unavailable for this recent CVE. Not present in CISA KEV, indicating no confirmed widespread exploitation, though SSRF vulnerabilities are frequently exploited once discovered due to low attack complexity. No public POC reference provided, but SSRF exploitation is well-documented and trivial given the vulnerability description. SSVC assessment: Exploitation status is public (vulnerability disclosed with patch), automatable (no user interaction required per UI:N), technical impact is partial (initial access to internal services), but mission impact depends entirely on what internal services are exposed - cloud environments with metadata endpoints face critical risk. Priority depends on deployment context: high-priority patch for cloud-hosted instances with access to sensitive internal networks, moderate for isolated development environments. The network-accessible, no-authentication attack profile combined with Changed scope makes this a genuine priority despite the CVE's Low impact ratings, which fail to capture SSRF's lateral movement potential. |
| Exploit ScenarioDerived | Remote attacker interacts with an OpenHarness-powered chatbot or AI agent, crafting prompts that cause the LLM to invoke web_fetch or web_search with attacker-controlled URLs targeting http://169.254.169.254/latest/meta-data/iam/security-credentials/ (AWS metadata endpoint). The agent executes the request from the server's network context, retrieves temporary IAM credentials, and returns them in the response or uses them for subsequent tool calls. Attacker escalates to full AWS account compromise using the exfiltrated credentials. Alternative scenario targets internal admin panels at http://localhost:8080/admin or private network services at http://192.168.1.10/config.json to map internal infrastructure and extract sensitive configuration data. |
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Alert meAnalysisAIv1 – Apr 17, 2026
Server-Side Request Forgery in OpenHarness AI agent framework (pre-commit bd4df81) permits remote unauthenticated attackers to manipulate web_fetch and web_search tool parameters, forcing the agent to make HTTP requests to internal infrastructure including RFC1918 private networks, localhost services, and cloud metadata endpoints (e.g., AWS EC2 169.254.169.254). Changed scope (S:C) in CVSS vector indicates potential for pivoting beyond the vulnerable application's trust boundary. EPSS data unavailable; no public exploit identified at time of analysis, though exploitation technique is well-understood for SSRF class vulnerabilities. Patch available via GitHub commit bd4df81.
RemediationAI
Upgrade to OpenHarness commit bd4df81f634f8c7cddcc3fdf7f561a13dcbf03ae or later from https://github.com/HKUDS/OpenHarness (patch confirmed via GitHub commit reference). The fix implements input validation on web_fetch and web_search tool parameters to block requests to private address ranges. For environments unable to immediately upgrade, disable the web_fetch and web_search tools entirely in agent configurations, which eliminates SSRF exposure but removes external web access capabilities from agents. Network-level compensating control: configure egress filtering to block outbound HTTP/HTTPS from OpenHarness processes to RFC1918 ranges (10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16), loopback (127.0.0.0/8), link-local (169.254.0.0/16), and cloud metadata endpoints (e.g., 169.254.169.254/32 for AWS/GCP/Azure); note this breaks legitimate use cases requiring internal HTTP access and may require allow-listing specific services. Application-level workaround: wrap web_fetch/web_search with a proxy that enforces allowlists of permitted external domains, though this requires code modification and careful maintenance of the allowlist to prevent bypasses.
Affected VersionsENISA
Affects your stack
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Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
OpenHarness is an AI agent framework (HKUDS project) that provides tool-calling capabilities to large language models. The vulnerable web_fetch and web_search tools execute HTTP requests on behalf of agents without validating destination addresses against SSRF protection lists. CWE-918 (Server-Side Request Forgery) occurs when applications accept user-controlled URLs and fetch them server-side without restricting access to internal resources. The Changed scope in CVSS:3.1/S:C indicates the vulnerability can affect resources beyond the vulnerable component's authorization scope - classic for SSRF where the server's network position grants access to resources unreachable from the attacker's position. Affected CPE cpe:2.3:a:hkuds:openharness identifies all versions prior to the patched commit. The vulnerability exploits the trust relationship between AI agents and their tool implementations, where LLM-generated parameters pass unchecked to network operations.
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Severity by source
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:L/VA:N/SC:H/SI:L/SA:L
Primary rating from Vendor (VulnCheck) · only source for this CVE.
CVSS VectorVendor: VulnCheck
Lifecycle Timeline
3DescriptionCVE.org
OpenHarness before commit bd4df81 contains a server-side request forgery vulnerability in the web_fetch and web_search tools that allows attackers to access private and localhost HTTP services by manipulating tool parameters without proper validation of target addresses. Attackers can influence an agent session to invoke these tools against loopback, RFC1918, link-local, or other non-public addresses to read response bodies from local development services, cloud metadata endpoints, admin panels, or other private HTTP services reachable from the victim host.
Executive ViewAI
OpenHarness AI agent framework versions prior to commit bd4df81 contain an unauthenticated Server-Side Request Forgery vulnerability that allows attackers to redirect the framework's web tools to access internal infrastructure, private networks, and cloud metadata endpoints, potentially exposing sensitive credentials and enabling lateral movement within your network. This affects any deployment using OpenHarness for AI agent operations and requires immediate patching to prevent credential theft and infrastructure reconnaissance.
Apply vendor patch. Interim mitigations if patch deployment is delayed: (1) Implement network-level egress controls blocking OpenHarness from accessing 127.0.0.1, 169.254.169.254, and all RFC1918 private address ranges (10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16); (2) Restrict OpenHarness service account IAM permissions to deny access to cloud metadata and credential retrieval APIs; (3) Disable or restrict the web_fetch and web_search tool parameters until patched; (4) Monitor outbound HTTP connections from OpenHarness processes for anomalous internal requests.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Server-Side Request Forgery exploits applications that fetch remote resources based on user-supplied URLs.
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EUVD-2026-23452
NVD
CVE.org
EPSS
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GitHub
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