Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
-
AccessReach GenAI prompt endpoint (network, unauthenticated)
-
DeliverySubmit prompt embedding Jinja2 template syntax
-
ExploitUnsanitized server-side template evaluation (SSTI)
-
ExecutionExecute arbitrary code on backend
-
ImpactFull compromise of server confidentiality, integrity, availability
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A05:2025 - Injection
ASVS 5.0
V1 - Encoding and Sanitization Code injection prevention, sandbox exec
MITRE ATT&CK
2 techniques across 2 tactics: Execution, Initial 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 that the target application be built on Open GenAI Stack (ogx-ai) and pass user-supplied prompt content into a Jinja2 template that is evaluated server-side without sanitization - i.e. the SSTI sink must be present in the request/prompt-handling path. Per the CVSS vector there is no authentication, user-interaction, or non-default-configuration requirement (AV:N/AC:L/PR:N/UI:N), so any attacker who can submit a prompt to an affected endpoint can trigger it. The primary real-world limiter is deployment scope: only systems actually running the vulnerable ogx-ai template-rendering path are exposed, and the claimed Meta/WhatsApp exposure is unconfirmed. |
| Impact | The CVSS 3.1 vector (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H = 9.8) describes an unauthenticated, network-reachable, low-complexity flaw yielding full code execution, which is internally consistent with CWE-94 and the RCE/Code Injection tags: a prompt-injection payload carrying Jinja2 template syntax reaches an unsanitized server-side template evaluation (classic SSTI), so the attacker's 'prompt' becomes executable server code. No EPSS score and no CISA KEV entry are present in the input, so there is no quantitative exploitation-probability signal and no confirmation of active exploitation. A researcher gist (abhi04anon) is referenced by NVD and most likely contains a writeup or working payload, so publicly available exploit code exists should be treated as likely rather than certain until the gist is verified. The key tension is the affected product: 'Open GenAI Stack (ogx-ai)' is an obscure open-source component, but the description claims it is 'used in the Meta AI backend for WhatsApp and other products' - an unverified, high-blast-radius assertion sourced only from the MITRE description, not from a vendor advisory or Meta confirmation. If true, this is a genuine critical-priority issue against a very large surface; if the Meta/WhatsApp linkage is speculative (as such 'as used in' claims often are), real-world exposure is limited to the niche ogx-ai deployments. Verify the WhatsApp/Meta claim and the gist contents with the vendor before treating this as a mass-exploitation priority. |
| Exploit ScenarioDerived | An attacker submits a chat/prompt input containing Jinja2 template syntax (e.g. {{7*7}} escalating to object-traversal payloads reaching os.system) to a GenAI endpoint built on ogx-ai; because the input is rendered server-side without sanitization, the template engine evaluates the expression and executes attacker-controlled code on the backend. No authentication or user interaction is required per the CVSS vector, and a referenced researcher gist likely provides a ready payload, lowering the skill barrier. |
Get an e-mail when this CVE is exploited, patched or re-scored. Free account.
Alert meAnalysisAIv1 – Sep 29, 2026
Unauthenticated remote code execution in Open GenAI Stack (ogx-ai, 2026-06-11 build) lets any attacker who can submit a prompt to an affected endpoint execute arbitrary server-side code, because prompt content is rendered as an unsanitized Jinja2 template (CWE-94, classic server-side template injection). The CVSS 3.1 vector is AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H (9.8), with no authentication, user-interaction, or non-default-configuration prerequisite, so exploitation reduces to reaching the vulnerable template-rendering path. No public exploit code has been identified at time of analysis, and the widely repeated claim that this stack underpins the Meta AI backend for WhatsApp is unconfirmed by any vendor advisory. Real-world risk is bounded by deployment scope: only systems actually running the vulnerable ogx-ai prompt-to-template path are exposed.
RemediationAI
No vendor-released patch or fixed version is identified in the available intelligence data, so confirm status with the ogx-ai upstream project and the NVD record at https://nvd.nist.gov/vuln/detail/CVE-2026-77177 before assuming a fix exists; the only public reference besides NVD/EUVD is an untyped gist at https://gist.github.com/abhi04anon/8ce0b68a5a7dda8a0501cbaf933173eb. The definitive remediation is architectural: stop passing untrusted prompt content into Jinja2 rendering, treating prompts strictly as data that are never compiled or rendered as templates, and if templating is genuinely required, render inside jinja2.sandbox.SandboxedEnvironment with a strict allowlist of variables and filters, accepting that sandboxes have a history of escapes and should never be the sole control. Actionable compensating controls, with their trade-offs: block or tightly restrict network reachability to prompt-handling endpoints via VPN, mTLS, or IP allowlisting (reduces the unauthenticated attack surface but limits legitimate client access); deploy WAF or input filtering for Jinja2 delimiters such as {{ }} and {% %} and common SSTI traversal patterns (fast to roll out but trivially bypassed through encoding or alternative syntax); run the ogx-ai process as an unprivileged user inside a container with a read-only filesystem, dropped Linux capabilities, seccomp profiles, and restricted egress (limits post-exploitation blast radius but does not prevent the initial code execution); and monitor for child-process creation or unusual outbound connections originating from the application process as a detection backstop. Because the flaw is unauthenticated (PR:N), authentication and access-management changes do not mitigate it on their own.
Affected VersionsENISA
Affects your stack
Find out whether the stacks and servers you run are on an affected version.
Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
Open GenAI Stack (ogx-ai) is a generative-AI application framework, and the affected build is dated 2026-06-11. The root cause class is CWE-94 code injection, realized here as server-side template injection (SSTI): user-supplied prompt text is placed into a Jinja2 template that the server evaluates, so Jinja2 expression syntax inside the prompt is interpreted by the template engine instead of being treated as inert data. Jinja2 exposes a deep traversal of the Python object model (dunder attributes, method calls and class navigation), which is what turns a simple expression-evaluation primitive into arbitrary command execution inside the server process. The assessed vector AV:N/AC:L/PR:N/UI:N confirms the sink is network-reachable with no authentication, no user interaction, and no special configuration, and the High confidentiality/integrity/availability ratings are consistent with full code execution rather than a contained information disclosure; the RCE and Code Injection tags and the EUVD record (EUVD-2026-89070) corroborate this. No CPE strings were supplied in the intelligence feed and EUVD lists the affected version range only as 'n/a n/a', so the precise vulnerable build boundary cannot be established from the available data and exposure must be determined by inventorying ogx-ai deployments that pass prompt content into the Jinja2 rendering path.
Know when Python gets its next vulnerability
- Watch products and get an email when something new is published
- Check this CVE against your own stack and servers
- Exploit and PoC references, threat intelligence from 22 sources
No credit card · 7-day full trial
Severity by source
AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
Unauthenticated network-reachable prompt reaches an unsanitized Jinja2 sink (AV:N/AC:L/PR:N/UI:N) yielding server code execution with full C/I/A impact within the same authority (S:U).
Primary rating from Vendor (mitre).
CVSS VectorVendor: mitre
Lifecycle Timeline
3DescriptionCVE.org
Open GenAI Stack (aka ogx-ai) 2026-06-11, as used in the Meta AI backend for WhatsApp and other products, allows code execution because prompt injection (with Jinja2 template syntax) can be used to achieve server-side expression evaluation without sanitization.
Articles & Coverage 1
Executive ViewAI
Open GenAI Stack (ogx-ai, 2026-06-11 build) carries a critical remote code execution flaw that lets an unauthenticated attacker who can reach a prompt-submitting endpoint run arbitrary code on the server, effectively handing over the host. No vendor patch is available and no public exploit has been identified at time of analysis, so the immediate risk is driven entirely by our own exposure: any internet- or partner-facing deployment of the affected prompt-to-template path is a full-compromise risk to the data, credentials, and downstream systems it touches. Leadership should focus on how many such instances we run, how reachable they are, and whether they run with privileges that would widen the blast radius.
No vendor-released patch identified at time of analysis. Interim mitigations: isolate or decommission internet-facing instances running the affected 2026-06-11 build; restrict network access to trusted client addresses and authenticated gateways; disable prompt-to-template (Jinja2) rendering or any feature that passes user-supplied prompt content into templates; wrap the rendering path with strict input validation or a sandboxed template engine; run the service with least privilege and no access to unrelated filesystems or cloud credentials; and monitor logs for template-injection and code-execution indicators.
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
Code injection occurs when an application accepts user input and passes it directly into a language interpreter or evaluator without proper sanitization.
Remote Code Execution represents the critical moment when an attacker successfully runs arbitrary code on a target system without physical access.
Wazuh SIEM platform versions 4.4.0 through 4.9.0 contain an unsafe deserialization vulnerability in the DistributedAPI t
BentoML version 1.4.2 and earlier contains an unauthenticated remote code execution vulnerability through insecure deser
pgAdmin 4 contains critical remote code execution vulnerabilities in the Query Tool download and Cloud Deployment endpoi
The renderLocalView function in render/views.py in graphite-web in Graphite 0.9.5 through 0.9.10 uses the pickle Python
BentoML is a Python library for building online serving systems optimized for AI apps and model inference. Rated critica
OpenSSL before 0.9.8za, 1.0.0 before 1.0.0m, and 1.0.1 before 1.0.1h does not properly restrict processing of ChangeCiph
pyLoad download manager version prior to 0.5.0b3.dev77 exposes the Flask SECRET_KEY through an unauthenticated endpoint.
Langflow (a visual LLM pipeline builder) contains a critical unauthenticated code execution vulnerability (CVE-2026-3301
In Mercurial before 4.1.3, "hg serve --stdio" allows remote authenticated users to launch the Python debugger, and conse
Unauthenticated remote code execution affects Kestra OSS (the open-source event-driven orchestration platform) prior to
Unauthenticated remote code execution in Marimo ≤0.20.4 allows attackers to execute arbitrary system commands via the `/
pyLoad is the free and open-source Download Manager written in pure Python. Rated medium severity (CVSS 5.3), this vulne
EUVD-2026-89070
GHSA-9rwh-q28c-cv6g
NVD
CVE.org
EPSS
Vulnrichment
Exploit-DB