Threat briefs

CVE-2025-71380 is an improper access control vulnerability (CWE-284) in n8n versions up to and including 1.114.4 that allows authenticated users to execute arbitrary commands on the underlying host system where n8n runs, potentially leading to data exfiltration, service disruption, or complete system compromise.

A vulnerability in `picklescan` versions prior to 0.0.34 (CVE-2025-71375) allows attackers to craft malicious Python pickle payloads using the `_operator.methodcaller` built-in function, which evades detection by the `picklescan` library and enables arbitrary code execution when the payload is loaded by an application using `pickle.load()`.

Remote attackers can bypass security checks in `picklescan` versions prior to 0.0.33 by crafting malicious pickle payloads utilizing `operator.methodcaller` function calls, which upon loading by systems relying on `picklescan` for validation, results in arbitrary code execution and system compromise.

CVE-2025-71372 describes a critical vulnerability in Picklescan versions prior to 0.0.33, where the tool fails to detect a specific numpy gadget in pickle `__reduce__` methods, allowing attackers to craft malicious pickle files that execute arbitrary Python code when loaded, bypassing safety checks and enabling supply-chain poisoning of shared model files.

A critical vulnerability, CVE-2025-71369, in `picklescan` versions prior to 0.0.28 allows remote attackers to bypass safety checks for malicious Python pickle files that utilize specific `torch.utils.data.datapipes` methods, enabling undetected embedded malicious code to execute during deserialization, which results in remote code execution (RCE) on the victim's system.

Picklescan versions prior to 0.0.34 contain a deserialization vulnerability (CVE-2025-71367) that allows remote attackers to bypass security checks by crafting malicious pickle files using `_operator.attrgetter` in reduce methods, leading to arbitrary code execution when `pickle.load()` processes the file.

A critical deserialization vulnerability (CVE-2025-71366) exists in picklescan versions prior to 0.0.28, allowing remote attackers to bypass safety checks by embedding malicious `torch.utils.bottleneck.__main__.run_cprofile` function calls in pickle files, leading to arbitrary code execution when victims load the crafted files.

picklescan versions prior to 0.0.33 are vulnerable to unsafe deserialization via CVE-2025-71362, allowing attackers to embed malicious code in pickle files that executes due to `numpy.f2py.crackfortran` calling `eval` on arbitrary strings when loaded from untrusted sources, leading to arbitrary code execution.

A high-severity deserialization of untrusted data vulnerability (CVE-2025-71360) in picklescan versions before 0.0.29 allows attackers to embed undetected remote command execution code within malicious pickle files, leading to arbitrary code execution when loaded by victims.

Picklescan versions prior to 0.0.29 are vulnerable to remote code execution (CVE-2025-71359) due to a failure in detecting malicious Python pickle payloads that utilize `lib2to3.pgen2.grammar.Grammar.loads`, allowing attackers to craft files that evade detection and execute arbitrary code during deserialization.

A critical deserialization vulnerability (CVE-2025-71356) in `picklescan` versions prior to 0.0.28 allows attackers to embed undetected malicious code within Python pickle files, leading to remote code execution when these files are loaded by victims.

Picklescan before version 0.0.28 contains a deserialization vulnerability where it fails to properly detect malicious pickle files. Attackers can craft these files with embedded code that exploits the `torch._dynamo.guards.GuardBuilder.get` function in reduce methods, leading to arbitrary command execution when loaded on a victim system.

A critical vulnerability (CVE-2025-71347) exists in picklescan prior to version 0.0.33, allowing remote attackers to bypass security checks by failing to detect malicious pickle files leveraging the numpy.f2py.crackfortran.param_eval function, leading to arbitrary code execution upon deserialization of untrusted data.

CVE-2025-71345 describes a critical vulnerability in `picklescan` versions prior to 0.0.30, where attackers can embed undetected malicious code within pickle files that specifically invoke the `torch.utils.bottleneck.__main__.run_autograd_prof` function, leading to remote code execution upon deserialization by bypassing `picklescan`'s security checks.

A deserialization vulnerability, CVE-2025-71343, in picklescan before version 0.0.30 allows attackers to craft malicious pickle files that evade detection and lead to arbitrary code execution when loaded via `pickle.load()`.

A critical vulnerability (CVE-2025-71342) exists in picklescan versions prior to 0.0.30, where it fails to detect malicious code embedded in Python pickle files by leveraging `idlelib.run.Executive.runcode` in reduce methods, allowing attackers to conceal and execute arbitrary code during `pickle.load` operations, leading to remote code execution (RCE) and potential supply chain attacks, particularly impacting PyTorch models.

A stack-based buffer overflow vulnerability (CVE-2026-14606) exists in RT-Thread versions up to 5.0.2, specifically in the `CAN_Receive` function of the SWM341 CAN Handler component, allowing for local exploitation via manipulation, with a public exploit available.

A stack-based buffer overflow vulnerability (CVE-2026-14605) exists in the `recvmsg` function of the `ls1c CAN Handler` component within RT-Thread up to version 5.0.2, requiring local access for exploitation and having a publicly available exploit, potentially leading to high impact on confidentiality, integrity, and availability.

A heap buffer overflow vulnerability (CVE-2026-58379) in GIMP's Paint Shop Pro (PSP) file format parser allows a remote attacker to achieve arbitrary code execution or cause a denial of service (DoS) by tricking a user into opening a specially crafted PSP image file, exploiting incorrect buffer size calculations when processing low bit-depth images.

The Qilin ransomware group, known for its Golang-based ransomware and double extortion tactics, has claimed a new victim in the Financial Services sector, www.tqfinancials.com, as part of its ongoing campaign, highlighting the persistent threat of data encryption and exfiltration.

A critical argument injection vulnerability (CVE-2026-14459) in TUBITAK BILGEM Software Technologies Research Institute's pardus-software versions up to 1.0.4 allows a local, low-privileged attacker to achieve unauthorized command execution, severely impacting confidentiality, integrity, and availability.

This brief describes the detection of suspicious `javaw.exe` execution on Windows systems by adversaries leveraging recently dropped or modified Java payloads from user-writable directories (e.g., `Users`, `ProgramData`, `Windows\Temp`) to establish command and control via immediate DNS lookups, thereby evading application control mechanisms.

Adversaries can exploit the creation of AWS Lambda event source mappings to establish stealthy persistence and execution, or to continuously siphon records from event sources like Amazon SQS, Kinesis, DynamoDB, MSK, Kafka, or MQ, by mapping an event source to an attacker-controlled Lambda function, enabling durable execution and data exfiltration without requiring further interactive access.

Adversaries may delete AWS Lambda functions to disrupt business operations, remove evidence of their presence, or impede incident response, an action detectable by monitoring for `DeleteFunction` calls in `aws.cloudtrail` logs and correlating with expected change windows.

This brief identifies the critical risk of an AWS Lambda layer's permission policy being modified, typically via the `AddLayerVersionPermission` API, to grant external AWS accounts, AWS Organizations, or the public access, potentially leading to the leakage of proprietary code or secrets and creating a supply-chain vector for attacker-influenced code execution in downstream functions.

Adversaries may establish a persistent, internet-reachable entry point by creating or updating an AWS Lambda function URL with an authentication type of NONE, allowing unauthenticated invocation for command and control, data exfiltration, or on-demand code execution, thereby bypassing the need for valid AWS credentials.

An adversary can establish persistence and defense evasion by modifying an AWS Lambda function's resource policy via the `AddPermission` API to grant `lambda:InvokeFunction` permissions to a principal in an external AWS account, enabling unauthorized function invocation and potential data exfiltration without altering function code.

Attackers can leverage the creation or renaming of Systemd override configuration files in standard or user service directories to achieve persistence or privilege escalation on Linux systems, altering service behavior to execute malicious commands during system startup or at predefined intervals via timers, thereby maintaining unauthorized access or evading detection.

This brief details the risk of VNC (Virtual Network Computing) traffic originating from internal networks and destined for the internet, indicating potential unauthorized access or a backdoor, as VNC is frequently exploited by threat actors when exposed externally via specific TCP ports (5800-5810).

This brief detects unauthorized Virtual Network Computing (VNC) traffic originating from the Internet and targeting internal network segments on TCP ports 5800-5810, indicating potential initial access or backdoor exploitation by threat actors leveraging exposed VNC services.