Avito Details Security Gates Implementation to Enforce Vulnerability Remediation Without Disrupting Developers
Avito has published an in-depth technical case study on implementing security gates that enforce vulnerability remediation policies while minimizing friction for development teams. Alexander Trifanov, head of Application Security at the company, describes nearly ten years of experience building controls that prevent SLA violations without turning security into a bottleneck.
The article defines a security gate as any automated check that can block or allow actions based on policy. Quality gates focus on code standards and functionality, while security gates target vulnerabilities and compliance. Both rely on a signal source, policy engine, and enforcement mechanism, but the latter protects against risk accumulation at company scale.
Trifanov explains that manual SLA extensions quickly erode control. Developers learn that deadlines can be moved, leading to repeated violations. A properly designed gate forces explicit risk acceptance by security before problematic actions proceed.
Pipeline Architecture and False-Positive Handling
Avito rejected synchronous scanner execution inside CI/CD pipelines. Instead, pushes trigger asynchronous orchestration of SAST, SCA, secret detection, and YAML configuration checks. Results are normalized in ASOC or SOAR, then automatically assigned to service owners with SLA-based priorities.
Each finding tracks three fields: status (active/inactive), verification_status (valid, false candidate, false positive), and verification_reason. Automated heuristics, validators, and limited AppSec review reduce noise before tasks reach developers.
Key requirements for any gate include robust false-positive workflows, deduplication of near-identical findings, and an emergency bypass switch. The bypass proved critical for business continuity during incidents.
First Gate at Deployment Stage
The initial gate queries SOAR at deployment time and blocks releases containing active vulnerabilities past SLA. High-severity issues trigger immediate blocks; medium-severity issues allow two full sprints before enforcement.
Services in maintenance mode rarely trigger gates because deployments are infrequent. Avito therefore created a manual “red button” that can block entire organizational units (groups of teams) from deploying any services until issues are addressed. The capability has never been used, yet its existence drives higher compliance.
Pre-receive Gate and Library Handling
A second, earlier gate uses server-side pre-receive hooks in GitHub, GitLab, and Bitbucket. Only fast scanners run within a strict ten-second limit. Rejected pushes return the finding identifier so developers can request false-positive validation.
Feedback revealed developers reluctant to pin library versions and analysts storing non-deployed code. These edge cases led to a dedicated library-update flow that scans requests before packages are fetched in development environments or CI/CD.
Kubernetes and Kyverno Experiments
Attempts to embed policy enforcement directly into Kubernetes using Kyverno are discussed as an ongoing direction for covering services that bypass traditional pipelines. The article concludes that multiple overlapping gates at different lifecycle stages reduce the impact of any single missed detection.
Related articles
Building Your First Home Network Lab: Essential Tools and Experiments to Understand Corporate Networks
A cybersecurity professional without network knowledge resembles a guard without a building blueprint, spotting alarms but unable to trace the intruder. Setting up a personal lab on a standard computer bridges this gap through virtualization and hands-on practice with protocols and attacks. The guide recommends GNS3 for topology emulation, VirtualBox or VMware for running Windows and Linux workstations, Cisco Packet Tracer for quick simulations, Wireshark for traffic analysis, and draw.io for diagramming. Key experiments include configuring Cisco IOS routers with IP addressing, testing default gateways, observing ARP requests and replies, triggering broadcast storms via switch loops, and enabling STP to prevent loops. The lab demonstrates how legacy protocols like ARP expose networks to spoofing and why segmentation with VLANs and firewalls matters. Resources from CyberED provide demo access to courses on SOC analysis, penetration testing, and AI applications in security to extend learning.
PSLC and Agent-Ops: From Product Support to Infrastructure Transformation
Sergey Zhitinsky, founder of Git in Sky, attended the OPS Talk by Sber meetup on October 19 and discussed the PSLC methodology with architect Alexander Shapovalov. PSLC, or Product Service Lifecycle, outlines two loops for restoring services immediately and improving reliability to prevent recurrence through teams, knowledge, and platform support. Agent-Ops focuses on eight detailed steps for individual infrastructure tasks: intention, evidence collection, diagnostics, planning, approval, controlled change, verification, and lessons learned. The article illustrates their complementary use in a scenario where post-release log growth fills a database disk, requiring both service restoration and root-cause fixes. Both approaches emphasize knowledge retention, action control, and human accountability, though Agent-Ops v0.5.1 mandates explicit human approval and separate execution for production changes. PSLC suits larger organizations with shared platforms, while Agent-Ops targets smaller teams handling infrastructure operations with AI agents.
Russian Organizations Allocate 4.5 Trillion Rubles to Innovation Spending in 2025
Large and medium-sized Russian organizations directed a total of 4.5 trillion rubles toward innovation activities during 2025. Nearly half of the expenditure originated from the services sector, while information technology and telecommunications accounted for 860.9 billion rubles. The Institute for Statistical Studies and Economics of Knowledge at HSE University published the figures based on Rosstat data, showing an innovation intensity rate of 2.7 percent. Services companies alone contributed approximately 2.3 trillion rubles, including 882.7 billion rubles for research and development. Astra Group IR Director Vladislav Anshakov outlined major spending areas such as product development, cloud and AI hardware, and acquisitions of technologies and teams. The group expanded its portfolio with the Perseus DBMS and a 26 percent stake in AI developer AIB. More than one-third of organizations cited high costs and insufficient internal funds as key barriers to further innovation.
Telegram macOS Developer Says 99.9% of Client Code Is Now Written by AI and Suggests Firing Manual Coders
Mike, the developer of the official Telegram client for macOS, stated that artificial intelligence now generates 99.9 percent of the messenger's client code. He argued that programmers who continue writing code manually should be dismissed. In a Telegram discussion, Mike cited the gram.org website as an example created entirely with AI assistance in a single day, with domain support from Pavel Durov. He also described adapting the iOS client for a foldable iPhone Duo overnight using Claude. According to Mike, even designers are now contributing to client code, and 80 to 90 percent of Telegram developers share his positive view of AI tools. When participants raised questions about code quality and security, Mike replied that AI also identifies and fixes vulnerabilities, claiming the resulting code is superior to human-written equivalents. He further announced plans to open a new GitHub repository for the macOS client source code, as the previous repository had not been updated for over a year.