OpenAEV is an open source platform allowing organizations to plan, schedule and conduct cyber adversary simulation campaign and tests. Starting in version 1.0.0 and prior to version 2.0.13, OpenAEV's password reset implementation contains multiple security weaknesses that together allow reliable account takeover. The primary issue is that password reset tokens do not expire. Once a token is generated, it remains valid indefinitely, even if significant time has passed or if newer tokens are issued for the same account. This allows an attacker to accumulate valid password reset tokens over time and reuse them at any point in the future to reset a victim’s password. A secondary weakness is that password reset tokens are only 8 digits long. While an 8-digit numeric token provides 100,000,000 possible combinations (which is secure enough), the ability to generate large numbers of valid tokens drastically reduces the required number of attempts to guess a valid password reset token. For example, if an attacker generates 2,000 valid tokens, the brute-force effort is reduced to approximately 50,000 attempts, which is a trivially achievable number of requests for an automated attack. (100 requests per second can mathematically find a valid password reset token in 500 seconds.) By combining these flaws, an attacker can mass-generate valid password reset tokens and then brute-force them efficiently until a match is found, allowing the attacker to reset the victim’s password to a value of their choosing. The original password is not required, and the attack can be performed entirely without authentication. This vulnerability enables full account takeover that leads to platform compromise. An unauthenticated remote attacker can reset the password of any registered user account and gain complete access without authentication. Because user email addresses are exposed to other users by design, a single guessed or observed email address is sufficient to compromise even administrator accounts with non-guessable email addresses. This design flaw results in a reliable and scalable account takeover vulnerability that affects any registered user account in the system. Note: The vulnerability does not require OpenAEV to have the email service configured. The exploit does not depend on the target email address to be a real email address. It just needs to be registered to OpenAEV. Successful exploitation allows an unauthenticated remote attacker to access sensitive data (such as the Findings section of a simulation), modify payloads executed by deployed agents to compromise all hosts where agents are installed (therefore the Scope is changed). Users should upgrade to version 2.0.13 to receive a fix.

Flowsint is an open-source OSINT graph exploration tool designed for cybersecurity investigation, transparency, and verification. Flowsint allows a user to create investigations, which are used to manage sketches and analyses. Sketches have controllable graphs, which are comprised of nodes and relationships. The sketches contain information on an OSINT target (usernames, websites, etc) within these nodes and relationships. The nodes can have automated processes execute on them called 'transformers'. A remote attacker can create a sketch, then trigger the 'org_to_asn' transform on an organization node to execute arbitrary OS commands as root on the host machine via shell metacharacters and a docker container escape. Commit b52cbbb904c8013b74308d58af88bc7dbb1b055c appears to remove the code that causes this issue.

Axios is a promise based HTTP client for the browser and Node.js. Prior to 1.15.0 and 0.3.1, the Axios library is vulnerable to a specific "Gadget" attack chain that allows Prototype Pollution in any third-party dependency to be escalated into Remote Code Execution (RCE) or Full Cloud Compromise (via AWS IMDSv2 bypass). This vulnerability is fixed in 1.15.0 and 0.3.1.

Certain HP DesignJet products may be vulnerable to information disclosure though printer's web interface allowing unauthenticated users to view sensitive print job information.

Insufficient input validation leading to memory overread when the NetScaler is configured as a Gateway (VPN virtual server, ICA Proxy, CVPN, RDP Proxy) OR AAA virtual server

CLIENT_CERT authentication does not fail as expected for some scenarios when soft fail is disabled vulnerability in Apache Tomcat, Apache Tomcat Native. This issue affects Apache Tomcat: from 11.0.0-M1 through 11.0.18, from 10.1.0-M7 through 10.1.52, from 9.0.83 through 9.0.115; Apache Tomcat Native: from 1.1.23 through 1.1.34, from 1.2.0 through 1.2.39, from 1.3.0 through 1.3.6, from 2.0.0 through 2.0.13. Users are recommended to upgrade to version Tomcat Native 1.3.7 or 2.0.14 and Tomcat 11.0.20, 10.1.53 and 9.0.116, which fix the issue.

A denial of service vulnerability exists in React Server Components, affecting the following packages: react-server-dom-parcel, react-server-dom-turbopack and react-server-dom-webpack (versions 19.0.0 through 19.0.4, 19.1.0 through 19.1.5, and 19.2.0 through 19.2.4). The vulnerability is triggered by sending specially crafted HTTP requests to Server Function endpoints.The payload of the HTTP request causes excessive CPU usage for up to a minute ending in a thrown error that is catchable.

vLLM is an inference and serving engine for large language models. In a multi-node vLLM deployment using the V0 engine, vLLM uses ZeroMQ for some multi-node communication purposes. The secondary vLLM hosts open a `SUB` ZeroMQ socket and connect to an `XPUB` socket on the primary vLLM host. When data is received on this `SUB` socket, it is deserialized with `pickle`. This is unsafe, as it can be abused to execute code on a remote machine. Since the vulnerability exists in a client that connects to the primary vLLM host, this vulnerability serves as an escalation point. If the primary vLLM host is compromised, this vulnerability could be used to compromise the rest of the hosts in the vLLM deployment. Attackers could also use other means to exploit the vulnerability without requiring access to the primary vLLM host. One example would be the use of ARP cache poisoning to redirect traffic to a malicious endpoint used to deliver a payload with arbitrary code to execute on the target machine. Note that this issue only affects the V0 engine, which has been off by default since v0.8.0. Further, the issue only applies to a deployment using tensor parallelism across multiple hosts, which we do not expect to be a common deployment pattern. Since V0 is has been off by default since v0.8.0 and the fix is fairly invasive, the maintainers of vLLM have decided not to fix this issue. Instead, the maintainers recommend that users ensure their environment is on a secure network in case this pattern is in use. The V1 engine is not affected by this issue.

A vulnerability has been identified in Solid Edge SE2025 (All versions < V225.0 Update 5). The affected applications contain an out of bounds read past the end of an allocated structure while parsing specially crafted PAR files. This could allow an attacker to execute code in the context of the current process.

A vulnerability has been identified in Solid Edge SE2025 (All versions < V225.0 Update 5). The affected applications contain an out of bounds read past the end of an allocated structure while parsing specially crafted PAR files. This could allow an attacker to execute code in the context of the current process.