CVE-2025-49521 is a high-severity vulnerability identified in the Event-Driven Ansible (EDA) component of the Red Hat Ansible Automation Platform 2.5 running on Red Hat Enterprise Linux 8. The flaw arises from improper control over the generation of code, specifically due to the evaluation of user-supplied Git branch or refspec values as Jinja2 templates. Jinja2 is a popular templating engine used in Python applications, and improper handling of template inputs can lead to code injection vulnerabilities. In this case, authenticated users can craft malicious inputs that are interpreted as Jinja2 expressions, enabling them to execute arbitrary commands or access sensitive files on the EDA worker node. This vulnerability extends to OpenShift environments where the exploitation can lead to theft of service account tokens, potentially allowing attackers to escalate privileges or move laterally within the cluster. The vulnerability has a CVSS v3.1 base score of 8.8, reflecting its high impact on confidentiality, integrity, and availability. The attack vector is network-based (AV:N), requires low attack complexity (AC:L), and only requires privileges (PR:L) but no user interaction (UI:N). The scope is unchanged (S:U), but the impact on confidentiality, integrity, and availability is high (C:H/I:H/A:H). No known exploits are reported in the wild yet, but the nature of the vulnerability and the criticality of the affected platform make it a significant risk. The vulnerability affects the Ansible Automation Platform 2.5 for RHEL 8, a widely used automation and orchestration tool in enterprise environments, especially for managing infrastructure as code and automating IT workflows.

For European organizations, this vulnerability poses a serious threat due to the widespread adoption of Red Hat Ansible Automation Platform in enterprise IT environments, including cloud infrastructure, DevOps pipelines, and hybrid cloud deployments. Exploitation could lead to unauthorized command execution on critical automation servers, resulting in data breaches, disruption of automated workflows, and potential compromise of entire IT environments. In OpenShift deployments, the risk is compounded by possible service account token theft, which can facilitate privilege escalation and lateral movement within Kubernetes clusters. This could impact sectors with high automation reliance such as finance, telecommunications, manufacturing, and public administration. The breach of confidentiality and integrity could lead to regulatory non-compliance under GDPR and other data protection laws, resulting in legal and financial penalties. Additionally, the availability impact could disrupt business-critical automation processes, causing operational downtime and loss of productivity.

Organizations should immediately apply patches or updates provided by Red Hat once available. In the absence of patches, administrators should restrict access to the EDA component to trusted users only and enforce strict authentication and authorization controls. Input validation and sanitization should be enhanced to prevent malicious Jinja2 template injection. Monitoring and logging of EDA worker activities should be increased to detect anomalous command executions or file access patterns. For OpenShift environments, service account tokens should be rotated regularly, and the principle of least privilege should be enforced on service accounts to limit the impact of token theft. Network segmentation can be employed to isolate automation platforms from sensitive parts of the infrastructure. Additionally, organizations should conduct security assessments and penetration testing focused on automation platforms to identify and remediate similar injection vulnerabilities proactively. Implementing runtime application self-protection (RASP) or Web Application Firewalls (WAF) with custom rules for Jinja2 template injection patterns may provide additional defense layers.