Vulnerabilities

FlowiseAI Flowise up to version 3.0.2 contains a server-side request forgery (SSRF) flaw in the Evaluations Endpoint, specifically in the axios.post call within packages/server/src/controllers/evaluations/index.ts. A remote attacker who manipulates the Host or X-Forwarded-Proto headers can trick the server into issuing requests toward attacker-influenced destinations, potentially reaching internal services, cloud metadata endpoints, or other network resources reachable from the Flowise host. The CVSS 4.0 vector indicates low privileges are required (PR:L), so an attacker needs at least limited authenticated access to the Flowise instance, and overall impact is rated low (2.1). Only Flowise versions that are no longer supported by the maintainer are affected, and a public exploit reference exists as a GitHub issue on the Flowise repository. EPSS is very low (0.2%, 12th percentile), the issue is not in the CISA KEV catalog, and no active exploitation in the wild has been reported.

Do: Upgrade Flowise to version 3.1.3 or later, which contains the patch (commit 700137738bcaebefd4709021f6d6b0abcd7df0ac); since affected versions are unsupported, running them long-term is not viable. If upgrading is delayed, restrict access to the evaluations endpoint to trusted authenticated users, avoid blindly trusting Host/X-Forwarded-Proto headers from untrusted proxies, and egress-filter the Flowise server so it cannot reach internal services or metadata endpoints. Review server logs for unexpected outbound requests originating from the evaluations controller as evidence of exploitation attempts.

Flowise versions before 3.1.4 contain a missing-authorization flaw (CWE-862) in the /api/v1/text-to-speech/abort endpoint, which accepts user-supplied chatflowId and chatId values without verifying that the requester owns the session. An unauthenticated remote attacker who knows or guesses valid identifiers can submit abort requests that terminate other users' active chatflow predictions, causing targeted service disruption. The impact is limited to availability of individual chat sessions (CVSS 4.0: 6.3, medium) with no confidentiality or integrity impact. Anyone running a self-hosted Flowise instance on a version prior to 3.1.4, especially one exposed to untrusted networks, is affected. Exploitation status: a public advisory/PoC reference exists, EPSS is very low (0.2%, 16th percentile), and the flaw is not in the CISA KEV catalog, so no in-the-wild exploitation is known.

Do: Upgrade Flowise to version 3.1.4 or later, where ownership verification for the abort endpoint is enforced. If immediate patching is not possible, place Flowise behind an authenticating reverse proxy or restrict network access so unauthenticated callers cannot reach /api/v1/text-to-speech/abort. Review application logs for abort requests referencing chatflowId/chatId values not associated with legitimate sessions as an indicator of abuse.

Tesseract OCR versions 5.5.3 and earlier contain a heap out-of-bounds write (CWE-787) in the LSTM recognition path: while earlier hardening added bounds checks to NetworkIO::CopyTimeStepGeneral and NetworkIO::Randomize, the NetworkIO::WriteTimeStepPart and NetworkIO::AddTimeStepPart functions in src/lstm/networkio.cpp remained unchecked. The flaw is triggered when the default LSTM engine processes a specially crafted .traineddata model file: in LSTM::Forward (src/lstm/lstm.cpp) the source_ buffer is sized from the independently deserialized na_ field, but WriteTimeStepPart writes a count driven by ns_ from the CI gate WeightMatrix dim1() value, so a crafted NT_LSTM layer with ns_ much larger than na_ overruns the heap buffer during the first recognition step. An attacker who can get such a model file processed gains heap corruption, causing a crash or potentially controlled memory corruption; CVSS 4.0 rates this 8.6 High with a local attack vector and no privileges or user interaction required. Anyone running Tesseract 5.5.3 or earlier is affected in principle, with practical risk concentrated in applications and pipelines that load third-party or otherwise untrusted .traineddata language models rather than only official trusted ones. No public proof-of-concept or in-the-wild exploitation is known, the flaw is not in CISA KEV, and no fixed release was available at the time of review.

Do: No fixed Tesseract release is available yet, so monitor the project for a patched version and upgrade as soon as one ships. Until then, avoid loading .traineddata files from untrusted or third-party sources on affected builds, verify the provenance and integrity of any externally sourced language models, and consider running OCR of external models in sandboxed, low-privilege workers to limit impact of a crash or heap corruption.

Flowise 3.1.2 contains an improper code generation control flaw (CWE-94, code injection) in its /api/v1/prediction/ API endpoint. A remote, unauthenticated attacker can send a crafted request to this endpoint to execute arbitrary code on the server hosting Flowise, achieving full confidentiality, integrity, and availability impact (CVSS 9.8) under the application's privileges. Only version 3.1.2 is named in the available data; the full range of affected versions and any patched release are not specified. As of the provided data, the issue is not listed in CISA's KEV and no public proof-of-concept or confirmed in-the-wild exploitation is known. The critical rating reflects that the flaw is network-reachable with no privileges or user interaction required.

Do: Inventory Flowise deployments and identify any running version 3.1.2; upgrade to a patched release as soon as the vendor publishes one (no fixed version is named in the current data), and monitor the Flowise GitHub repository for an official advisory. Until patched, restrict access to /api/v1/prediction/ by enforcing authentication, binding the service to internal interfaces, or adding reverse-proxy/firewall rules. Review logs for unexpected or unauthenticated requests to that endpoint as a sign of probing or exploitation.

CVE-2026-84869 is a critical authorization flaw (CWE-862 missing authorization, CWE-269 improper privilege management) in the ScreenConnect client, the endpoint-side agent of ConnectWise's widely used remote access and remote support platform, in which files can be transferred to a machine and executed during an active remote session without the expected authorization or without confirmation by the Host (technician). It is triggered in certain circumstances during an active session, with a network attack vector, low attack complexity, low privileges required, and no user interaction per the CVSS 3.1 vector. An actor who obtains or already holds access to a session context could thereby push and run files on the managed endpoint, potentially achieving code execution with high confidentiality, integrity, and availability impact (CVSS 3.1 score 9.9, scope changed). Only endpoints running the ScreenConnect client are affected; ScreenConnect servers are not impacted, and the affected client version ranges are governed by ConnectWise security advisory AV26-903 (not enumerated in the available data). The flaw is not currently known to be exploited: it is not in CISA KEV, no public proof of concept is known, and EPSS assigns a modest 0.4% probability of exploitation within the next 30 days (32nd percentile).

Do: Follow ConnectWise security advisory AV26-903 and update ScreenConnect clients to the patched version it specifies, noting that ScreenConnect servers do not require remediation. Until patching is complete, monitor active remote sessions, require Host confirmation for file transfers, and review recent sessions on high-value endpoints for unexpected transferred or executed files; given no known exploitation and the active-session prerequisite, prioritize endpoints routinely accessed remotely.