OpenClaw before 2026.3.31 contains a decompression bomb vulnerability in image processing that fails to properly enforce pixel-limit guards on sips. Attackers can exploit this by uploading oversized images to cause denial of service through excessive memory consumption.
OpenClaw before 2026.3.31 contains an authentication rate limiting bypass vulnerability that allows attackers to circumvent shared authentication protections using fake device tokens. Attackers can exploit the mixed WebSocket authentication flow to bypass rate limiting controls and conduct brute force attacks against weak shared passwords.
OpenClaw before 2026.3.28 contains an environment variable sanitization vulnerability where GIT_TEMPLATE_DIR and AWS_CONFIG_FILE are not blocked in the host-env blocklist. Attackers can exploit approved exec requests to redirect git or AWS CLI behavior through attacker-controlled configuration files to execute untrusted code or load malicious credentials.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the GraphCypherQAChain node forwards user-provided input directly into the Cypher query execution pipeline without proper sanitization. An attacker can inject arbitrary Cypher commands that are executed on the underlying Neo4j database, enabling data exfiltration, modification, or deletion. This vulnerability is fixed in 3.1.0.
A request smuggling vulnerability exists in libsoup's HTTP/1 header parsing logic. The soup_message_headers_append_common() function in libsoup/soup-message-headers.c unconditionally appends each header value without validating for duplicate or conflicting Content-Length fields. This allows an attacker to send HTTP requests containing multiple Content-Length headers with differing values.
KTransformers through 0.5.3 contains an unsafe deserialization vulnerability in the balance_serve backend mode where the scheduler RPC server binds a ZMQ ROUTER socket to all interfaces with no authentication and deserializes incoming messages using pickle.loads() without validation. Attackers can send a crafted pickle payload to the exposed ZMQ socket to execute arbitrary code on the server with the privileges of the ktransformers process.
radare2-mcp version 1.6.0 and earlier contains an os command injection vulnerability that allows remote attackers to execute arbitrary commands by bypassing the command filter through shell metacharacters in user-controlled input passed to r2_cmd_str(). Attackers can inject shell metacharacters through the jsonrpc interface parameters to achieve remote code execution on the host running radare2-mcp without requiring authentication.
radare2 prior to 6.1.4 contains a path traversal vulnerability in its project notes handling that allows attackers to read or write files outside the configured project directory by importing a malicious .zrp archive containing a symlinked notes.txt file. Attackers can craft a .zrp archive with a symlinked notes.txt that bypasses directory confinement checks, allowing note operations to follow the symlink and access arbitrary files outside the dir.projects root directory.
radare2 prior to 6.1.4 contains a path traversal vulnerability in project deletion that allows local attackers to recursively delete arbitrary directories by supplying absolute paths that escape the configured dir.projects root directory. Attackers can craft absolute paths to project marker files outside the project storage boundary to cause recursive deletion of attacker-chosen directories with permissions of the radare2 process, resulting in integrity and availability loss.
A weakness in SpiceJet’s public booking retrieval page permits full passenger booking details to be accessed using only a PNR and last name, with no authentication or verification mechanisms. This results in exposure of extensive personal, travel, and booking metadata to any unauthenticated user who can obtain or guess those basic inputs. The issue arises from improper access control on a sensitive data retrieval function.
A vulnerability in SpiceJet’s booking API allows unauthenticated users to query passenger name records (PNRs) without any access controls. Because PNR identifiers follow a predictable pattern, an attacker could systematically enumerate valid records and obtain associated passenger names. This flaw stems from missing authorization checks on an endpoint intended for authenticated profile access.
SWUpdate contains an integer underflow vulnerability in the multipart upload parser in mongoose_multipart.c that allows unauthenticated attackers to cause a denial of service by sending a crafted HTTP POST request to /upload with a malformed multipart boundary and controlled TCP stream timing. Attackers can trigger an integer underflow in the mg_http_multipart_continue_wait_for_chunk() function when the buffer length falls within a specific range, causing an out-of-bounds heap read past the allocated receive buffer to a local IPC socket.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the text-to-speech generation endpoint (POST /api/v1/text-to-speech/generate) is whitelisted (no auth) and accepts a credentialId directly in the request body. When called without a chatflowId, the endpoint uses the provided credentialId to decrypt the stored credential (e.g., OpenAI or ElevenLabs API key) and generate speech. This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the GET /api/v1/public-chatflows/:id endpoint returns the full chatflow object without sanitization for public chatflows. Docker validation revealed this is worse than initially assessed: the sanitizeFlowDataForPublicEndpoint function does NOT exist in the released v3.0.13 Docker image. Both public-chatflows AND public-chatbotConfig return completely raw flowData including credential IDs, plaintext API keys, and password-type fields. This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, a Mass Assignment vulnerability in the DocumentStore creation endpoint allows authenticated users to control the primary key (id) and internal state fields of DocumentStore entities. Because the service uses repository.save() with a client-supplied primary key, the POST create endpoint behaves as an implicit UPSERT operation. This enables overwriting existing DocumentStore objects. In multi-workspace or multi-tenant deployments, this can lead to cross-workspace object takeover and broken object-level authorization (IDOR), allowing an attacker to reassign or modify DocumentStore objects belonging to other workspaces. This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, this vulnerability allows remote attackers to bypass authentication on affected installations of FlowiseAI Flowise. Authentication is not required to exploit this vulnerability. The specific flaw exists within the resetPassword method of the AccountService class. There is no check performed to ensure that a password reset token has actually been generated for a user account. By default the value of the reset token stored in a users account is null, or an empty string if they've reset their password before. An attacker with knowledge of the user's email address can submit a request to the "/api/v1/account/reset-password" endpoint containing a null or empty string reset token value and reset that user's password to a value of their choosing. This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the password reset functionality on cloud.flowiseai.com sends a reset password link over the unsecured HTTP protocol instead of HTTPS. This behavior introduces the risk of a man-in-the-middle (MITM) attack, where an attacker on the same network as the user (e.g., public Wi-Fi) can intercept the reset link and gain unauthorized access to the victim’s account. This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, Flowise contains an authentication bypass vulnerability that allows an unauthenticated attacker to obtain OAuth 2.0 access tokens associated with a public chatflow. By accessing a public chatflow configuration endpoint, an attacker can retrieve internal workflow data, including OAuth credential identifiers, which can then be used to refresh and obtain valid OAuth 2.0 access tokens without authentication. This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the core security wrappers (secureAxiosRequest and secureFetch) intended to prevent Server-Side Request Forgery (SSRF) contain multiple logic flaws. These flaws allow attackers to bypass the allow/deny lists via DNS Rebinding (Time-of-Check Time-of-Use) or by exploiting the default configuration which fails to enforce any deny list. This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, a Server-Side Request Forgery (SSRF) vulnerability exists in FlowiseAI's POST/GET API Chain components that allows unauthenticated attackers to force the server to make arbitrary HTTP requests to internal and external systems. By injecting malicious prompt templates, attackers can bypass the intended API documentation constraints and redirect requests to sensitive internal services, potentially leading to internal network reconnaissance and data exfiltration. This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, a Server-Side Request Forgery (SSRF) protection bypass vulnerability exists in the Custom Function feature. While the application implements SSRF protection via HTTP_DENY_LIST for axios and node-fetch libraries, the built-in Node.js http, https, and net modules are allowed in the NodeVM sandbox without equivalent protection. This allows authenticated users to bypass SSRF controls and access internal network resources (e.g., cloud provider metadata services) This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the Chatflow configuration file upload settings can be modified to allow the application/javascript MIME type. This lets an attacker upload .js files even though the frontend doesn’t normally allow JavaScript uploads. This enables attackers to persistently store malicious Node.js web shells on the server, potentially leading to Remote Code Execution (RCE). This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, Flowise is vulnerable to a critical unauthenticated remote command execution (RCE) vulnerability. It can be exploited via a parameter override bypass using the FILE-STORAGE:: keyword combined with a NODE_OPTIONS environment variable injection. This allows for the execution of arbitrary system commands with root privileges within the containerized Flowise instance, requiring only a single HTTP request and no authentication or knowledge of the instance. This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, an improper mass assignment (JSON injection) vulnerability in the account registration endpoint of Flowise Cloud allows unauthenticated attackers to inject server-managed fields and nested objects during account creation. This enables client-controlled manipulation of ownership metadata, timestamps, organization association, and role mappings, breaking trust boundaries in a multi-tenant environment. This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, /api/v1/public-chatbotConfig/:id ep exposes sensitive data including API keys, HTTP authorization headers and internal configuration without any authentication. An attacker with knowledge just of a chatflow UUID can retrieve credentials stored in password type fields and HTTP headers, leading to credential theft and more. This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the specific flaw exists within the run method of the Airtable_Agents class. The issue results from the lack of proper sandboxing when evaluating an LLM generated python script. Using prompt injection techniques, an unauthenticated attacker with the ability to send prompts to a chatflow using the Airtable Agent node may convince an LLM to respond with a malicious python script that executes attacker controlled commands on the flowise server. This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the specific flaw exists within the run method of the CSV_Agents class. The issue results from the lack of proper sandboxing when evaluating an LLM generated python script. An attacker can leverage this vulnerability to execute code in the context of the user running the server. Using prompt injection techniques, an unauthenticated attacker with the ability to send prompts to a chatflow using the CSV Agent node may convince an LLM to respond with a malicious python script that executes attacker controlled commands on the Flowise server. This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, there is a remote code execution vulnerability in AirtableAgent.ts caused by lack of input verification when using Pandas. The user’s input is directly applied to the question parameter within the prompt template and it is reflected to the Python code without any sanitization. This vulnerability is fixed in 3.1.0.
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, The CSVAgent allows providing a custom Pandas CSV read code. Due to lack of sanitization, an attacker can provide a command injection payload that will get interpolated and executed by the server. This vulnerability is fixed in 3.1.0.
LeRobot through 0.5.1 contains an unsafe deserialization vulnerability in the async inference pipeline where pickle.loads() is used to deserialize data received over unauthenticated gRPC channels without TLS in the policy server and robot client components. An unauthenticated network-reachable attacker can achieve arbitrary code execution on the server or client by sending a crafted pickle payload through the SendPolicyInstructions, SendObservations, or GetActions gRPC calls.
Intrado 911 Emergency Gateway (EGW) 5.x, 6.x, and 7.x contain a path traversal vulnerability in the download_debuglog_file.php endpoint used for Debug Logs downloads. An unauthenticated attacker can manipulate the name parameter to read arbitrary files outside the intended directory.
Mastodon is a free, open-source social network server based on ActivityPub. Prior to v4.5.9, v4.4.16, and v4.3.22, Mastodon allows restricting new user sign-up based on e-mail domain names, and performs basic validation on e-mail addresses, but fails to restrict characters that are interpreted differently by some mailing servers. This vulnerability is fixed in v4.5.9, v4.4.16, and v4.3.22.
elFinder is an open-source file manager for web, written in JavaScript using jQuery UI. Prior to 2.1.67, elFinder contains a command injection vulnerability in the resize command. The bg (background color) parameter is accepted from user input and passed through image resize/rotate processing. In configurations that use the ImageMagick CLI backend, this value is incorporated into shell command strings without sufficient escaping. An attacker able to invoke the resize command with a crafted bg value may achieve arbitrary command execution as the web server process user. This vulnerability is fixed in 2.1.67.
Contour is a Kubernetes ingress controller using Envoy proxy. From v1.19.0 to before v1.33.4, v1.32.5, and v1.31.6, Contour's Cookie Rewriting feature is vulnerable to Lua code injection. An attacker with RBAC permissions to create or modify HTTPProxy resources can craft a malicious value in spec.routes[].cookieRewritePolicies[].pathRewrite.value or spec.routes[].services[].cookieRewritePolicies[].pathRewrite.value that results in arbitrary code execution in the Envoy proxy. The cookie rewriting feature is internally implemented using Envoy's HTTP Lua filter. User-controlled values are interpolated into Lua source code using Go text/template without sufficient sanitization. The injected code only executes when processing traffic on the attacker's own route, which they already control. However, since Envoy runs as shared infrastructure, the injected code can also read Envoy's xDS client credentials from the filesystem or cause denial of service for other tenants sharing the Envoy instance. This vulnerability is fixed in v1.33.4, v1.32.5, and v1.31.6.
pretalx is a conference planning tool. Prior to 2026.1.0, The organiser search in the pretalx backend rendered submission titles, speaker display names, and user names/emails into the result dropdown using innerHTML string interpolation. Any user who controls one of those fields (which includes any registered user whose display name is looked up by an administrator) could include HTML or JavaScript that would execute in an organiser's browser when the organiser's search query matched the malicious record. This vulnerability is fixed in 2026.1.0.
@node-oauth/oauth2-server is a module for implementing an OAuth2 server in Node.js. The token exchange path accepts RFC7636-invalid code_verifier values (including one-character strings) for S256 PKCE flows. Because short/weak verifiers are accepted and failed verifier attempts do not consume the authorization code, an attacker who intercepts an authorization code can brute-force code_verifier guesses online until token issuance succeeds.
Mako is a template library written in Python. Prior to 1.3.11, TemplateLookup.get_template() is vulnerable to path traversal when a URI starts with // (e.g., //../../../secret.txt). The root cause is an inconsistency between two slash-stripping implementations. Any file readable by the process can be returned as rendered template content when an application passes untrusted input directly to TemplateLookup.get_template(). This vulnerability is fixed in 1.3.11.
The AWS X-Ray Remote Sampler package provides a sampler which can get sampling configurations from AWS X-Ray. Prior to 0.1.0-alpha.8, OpenTelemetry.Sampler.AWS reads unbounded HTTP response bodies from a configured AWS X-Ray remote sampling endpoint into memory. AWSXRaySamplerClient.DoRequestAsync called HttpClient.SendAsync followed by ReadAsStringAsync(), which materializes the entire HTTP response body into a single in-memory string with no size limit. The sampling endpoint is configurable via AWSXRayRemoteSamplerBuilder.SetEndpoint (default: http://localhost:2000). An attacker who controls the configured endpoint, or who can intercept traffic to it (MitM), can return an arbitrarily large response body. This causes unbounded heap allocation in the consuming process, leading to high transient memory pressure, garbage-collection stalls, or an OutOfMemoryException that terminates the process. This vulnerability is fixed in 0.1.0-alpha.8.
OpenTelemetry dotnet is a dotnet telemetry framework. In 1.6.0-rc.1 and earlier, OpenTelemetry.Exporter.Jaeger may allow sustained memory pressure when the internal pooled-list sizing grows based on a large observed span/tag set and that enlarged size is reused for subsequent allocations. Under high-cardinality or attacker-influenced telemetry input, this can increase memory consumption and potentially cause denial of service. There is no plan to fix this issue as OpenTelemetry.Exporter.Jaeger was deprecated in 2023.
OpenTelemetry dotnet is a dotnet telemetry framework. In OpenTelemetry.Api 0.5.0-beta.2 to 1.15.2 and OpenTelemetry.Extensions.Propagators 1.3.1 to 1.15.2, The implementation details of the baggage, B3 and Jaeger processing code in the OpenTelemetry.Api and OpenTelemetry.Extensions.Propagators NuGet packages can allocate excessive memory when parsing which could create a potential denial of service (DoS) in the consuming application. This vulnerability is fixed in 1.15.3.
Argo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes. From 3.6.5 to 4.0.4, an unchecked array index in the pod informer's podGCFromPod() function causes a controller-wide panic when a workflow pod carries a malformed workflows.argoproj.io/pod-gc-strategy annotation. Because the panic occurs inside an informer goroutine (outside the controller's recover() scope), it crashes the entire controller process. The poisoned pod persists across restarts, causing a crash loop that halts all workflow processing until the pod is manually deleted. This vulnerability is fixed in 4.0.5 and 3.7.14.
This vulnerability allows an attacker to create a junction, enabling the deletion of arbitrary files with SYSTEM privileges. As a result, this condition potentially facilitates arbitrary code execution, whereby an attacker may exploit the vulnerability to execute malicious code with elevated SYSTEM privileges.
An issue was discovered in ToToLink A3300R firmware v17.0.0cu.557_B20221024 allowing attackers to execute arbitrary commands via the interval parameter to /cgi-bin/cstecgi.cgi.