CyberAttack.ai

By CyberAttack.aiBusiness Entrepreneurship Technology

CyberAttack.ai episodes

September 08Container Escape via Kernel Modules: Real Exploits, Real Risk
Container technology has transformed how software is built and deployed, but a critical misconception persists in many engineering and security teams: containers are not the same as virtual machines, and they do not provide the same level of isolation. Because containers share the host's kernel, a determined attacker who gains a foothold inside a container has a direct path to the most privileged layer of the entire system. This episode of Cybersecurity examines that path in detail — from initial compromise to full host takeover — using the lens of this deep-dive technical breakdown of kernel module exploitation in containerized environments as its foundation.
The episode walks through how container escape via kernel modules unfolds in practice, why it's so difficult to detect, and what concrete steps defenders can take today. Key topics include:
How kernel modules work — and why their unrestricted, kernel-level execution privilege makes them an ideal attacker target once container boundaries are breached.

The three-stage attack chain: gaining a foothold in a container, escalating privileges to reach kernel interfaces, and loading or tampering with a kernel module to achieve arbitrary code execution on the host.

Why detection is so hard — malicious modules operate at the same privilege level as the kernel itself, allowing attackers to suppress logs, hide processes, and hook system calls while remaining invisible to conventional monitoring tools.

The misconfigurations that open the door: containers running as root, overly permissive Linux capabilities (especially CAP_SYS_MODULE), disabled or misconfigured mandatory access controls like SELinux and AppArmor, and long-unpatched kernels.

Practical defensive measures: enforcing least-privilege container configurations, disabling dynamic kernel module loading on stable production systems, enabling seccomp profiles and mandatory access controls, and maintaining aggressive kernel patching cadences.

The role of kernel-level visibility — why organizations need monitoring that can surface unexpected module loads and anomalous system calls, the kind of deep host insight that endpoint monitoring at the kernel layer makes possible.
The episode also emphasizes the human dimension: developers need to understand why running containers as root is dangerous, not just that it's discouraged, and security teams need to make secure defaults enforceable rather than advisory. A container that has been granted CAP_SYS_MODULE and sits on an unpatched kernel is not a hardened workload — it's an open invitation. Organizations looking to identify and close these kinds of exposures systematically can explore vulnerability management tooling built for modern cloud-native environments.
For more on attacker tradecraft and evasion techniques, check out the related episode C2 Obfuscation: How Attackers Hide in Plain Sight — and How to Stop Them, which covers how threat actors conceal command-and-control communications once they've established persistence.
CyberAttack.ai
10 min
September 07C2 Obfuscation: How Attackers Hide in Plain Sight — and How to Stop Them
Once an attacker is inside a network, the breach itself is almost beside the point — what matters is the Command-and-Control channel keeping the operation alive. This episode of Cybersecurity dissects the sophisticated obfuscation techniques modern threat actors use to hide that C2 traffic from defenders, drawing on this in-depth CyberAttack.ai analysis of C2 obfuscation tactics and defenses. The conversation goes beyond naming techniques to explaining why each one works, where defenders are most exposed, and what practical countermeasures can shift the odds back toward the blue team.
The episode walks through six obfuscation methods that security teams are contending with right now — and the responses that can actually move the needle:
Domain fronting: Attackers route malicious traffic through trusted CDN infrastructure so firewalls see only a clean, whitelisted domain. The fix is granular allow-lists and TLS inspection paired with JA3 fingerprinting — not blanket CDN exemptions.

Protocol masquerading: C2 payloads are wrapped to look like routine HTTP requests, complete with convincing user-agent strings and JSON responses. Behavioral baselining exposes the mechanical regularity that legitimate browser traffic never has.

Layered encryption: DNS-over-HTTPS, gRPC over HTTP/2, and custom certificates stack into what the source article calls a "Matryoshka doll" of obfuscation. Defenders must force internal DNS resolution and upgrade sensors to parse HTTP/2 frame anomalies.

Fast-flux networks and DGAs: Malware cycles through algorithmically generated domains and constantly shifting IPs, making blacklists obsolete. Machine-learned DGA classifiers and passive DNS enrichment — watching for NXDOMAIN bursts followed by sudden successful lookups — are far more effective.

Living off trusted SaaS platforms: Attackers abuse Microsoft Teams, Slack, Google Sheets, and similar services to relay commands through ports no organization will block. A Cloud Access Security Broker (CASB) that can parse SaaS API behavior, combined with least-privilege OAuth scopes, is the practical line of defense — and robust endpoint monitoring helps surface the process-level activity that precedes these outbound calls.

Low-and-slow beaconing: A C2 channel that checks in only a few times a day produces almost no volume-based alert signal. Retaining flow logs for at least 30 days and shifting to regularity-based statistical models — hunting for packets of identical size on an inhuman schedule — is what makes these campaigns visible.
The episode closes with a practical integration framework: inventory and baseline before relying on ML or graph analytics, reduce outbound attack surface by restricting unnecessary geographies and autonomous system numbers, and layer network and endpoint detection so two independent data sources must agree before an alert fires. An AI security analyst can accelerate correlation across those data sources, helping teams catch the multi-technique campaigns — combining domain fronting, DNS-over-HTTPS, and low-frequency gRPC beaconing in a single intrusion — that no single tool is designed to catch alone. SOAR automation and pre-approved incident response runbooks, including procedures for blocking even business-critical SaaS when necessary, round out the defensive posture.
For more on related topics, check out the episode Securing the Invisible: Cloud-Native Best Practices for Serverless Architectures, which explores another frontier where attacker-controlled channels can be difficult to detect and contain.
CyberAttack.ai
11 min
September 06Securing the Invisible: Cloud-Native Best Practices for Serverless Architectures
Serverless computing has fundamentally changed how software is built, but it hasn't changed who is responsible for securing it. This episode of Cybersecurity takes a hard look at the security risks hiding inside serverless architectures — and the specific controls that distinguish well-defended cloud environments from the ones making headlines. The conversation draws on CyberAttack.ai's guide to securing serverless architectures, bringing its technical depth to a broader audience navigating the realities of cloud-native development.
The episode covers the full spectrum of serverless security — from identity and access management to runtime protection — giving teams a practical framework they can act on immediately:
IAM and least privilege at scale: Serverless environments can involve hundreds of individual functions, each requiring its own permissions. The episode explores why overly broad IAM roles are one of the most common and dangerous shortcuts developers take under deadline pressure — and how automated tools can audit permissions at scale before attackers exploit the gaps. Organizations looking for continuous visibility across their attack surface will recognize why IAM hygiene is inseparable from broader exposure management.

API Gateway configuration: The gateway is the front door to a serverless application, and a misconfigured one is effectively an open invitation. The episode covers proper authentication enforcement — OAuth, correctly handled JWTs, rate limiting — and why custom auth implementations are where subtle, costly bugs tend to take root.

Secure code practices in CI/CD pipelines: Speed is the point of serverless, but without static analysis and code review built into the pipeline from the start, insecure code ships at the same velocity as everything else. Runtime protection agents that monitor function behavior during execution add another critical layer.

Dependency and supply chain risk: Modern serverless functions run on ecosystems of third-party libraries and open-source packages. Dependency scanning on every build is non-negotiable — supply chain attacks have become a dominant threat vector, and serverless environments are not exempt.

Data protection defaults: Misconfigured cloud storage has been behind some of the most damaging breaches across healthcare, finance, and government. The episode makes the case that encryption at rest and in transit — and strict bucket policies — must be defaults, not afterthoughts. Teams managing cloud security posture will find this section particularly grounded in real-world failure patterns.

Logging, alerting, and cold-start risk: Ephemeral functions make traditional monitoring approaches unreliable. The episode explains how to instrument logging from day one, why alerting without anomaly detection is just archaeology, and how the cold-start window introduces a subtle but real risk of running outdated or unpatched code after a period of dormancy.
The throughline is the shared responsibility model — and the places where organizations consistently misread it. The cloud provider handles infrastructure. Everything above that layer — application logic, identity, data, and supply chain — belongs to the organization building on top of it. For more on how cloud misconfigurations create systemic exposure, the episode Cloud Misconfigurations: The #1 Cause of Breaches and How to Fight Back pairs directly with today's discussion.
CyberAttack.ai
9 min
September 05Cloud Misconfigurations: The #1 Cause of Breaches and How to Fight Back
Despite more than a decade of public cloud adoption, misconfigurations continue to top the list of root causes behind major data breaches. This episode of Cybersecurity digs into the structural and human reasons why organizations keep making the same cloud security mistakes at scale — and lays out a practical framework for catching and fixing them before attackers do. The discussion draws directly from this in-depth analysis of cloud misconfiguration risks and defenses published by CyberAttack.ai.
Here's what the episode covers:
Why complexity is the root problem: Modern cloud environments span multiple providers, services, and integrations — creating an attack surface that grows with every new permission granted and every new resource provisioned.

The cognitive load crisis: Engineers aren't careless — they're overwhelmed. Without serious automation and tooling, tracking every IAM permission, resource dependency, and configuration change across a dynamic environment is simply beyond what teams can realistically manage.

The most common offenders: Overly permissive IAM roles (where "we'll clean it up later" becomes never), publicly exposed storage buckets and open ports, and ghost infrastructure — forgotten test environments with wide-open security groups and unrotated credentials that quietly become permanent backdoors.

Real-world consequences: The 2019 Capital One breach is examined as a case study — a combination of Server-Side Request Forgery and an overprivileged IAM role led to the exfiltration of over 100 million records. Misconfigured, unauthenticated Elasticsearch clusters are cited as another chronic source of mass data exposure.

Policy as code and continuous automation: Shifting from console-clicking to infrastructure-as-code tools (Terraform, CloudFormation) combined with policy frameworks like Open Policy Agent allows security posture to be version-controlled, reviewed, and enforced automatically in CI/CD pipelines. Automated scanning tools should run on every deploy — not quarterly.

Secrets management as a non-negotiable: Hardcoded credentials in codebases are a breach waiting to happen. The episode advocates for dedicated secrets managers, regular rotation, and access auditing — and notes that proper cloud security practice treats secrets hygiene as foundational, not optional.
The episode's central argument is that misconfigurations and configuration drift are inevitable — the organizations that avoid breach headlines are the ones that build systems to catch mistakes automatically, enforce least privilege consistently, and treat vulnerability management as a continuous process rather than a periodic audit. None of it is glamorous, but all of it works.
For more on this theme, the episode Cloud Egress Control: Policy-as-Code for Secure Runtime Traffic pairs well as a follow-up listen. Misconfigurations exposed to the internet show up first in attack surface monitoring.
CyberAttack.ai
9 min
September 04Cloud Egress Control: Policy-as-Code for Secure Runtime Traffic
Outbound cloud traffic rarely gets the scrutiny it deserves, yet every uncontrolled egress path is a potential data exfiltration lane, a misconfigured secret leak, or a compliance landmine. This episode of Cybersecurity tackles the engineering and cultural challenge of locking down runtime egress using policy-as-code — a discipline that goes well beyond traditional firewall rules. It draws on CyberAttack.ai's deep-dive guide on cloud egress control and policy-as-code to deliver a framework that security and platform teams can act on immediately.
Here's what the episode covers:
Why egress is harder than it looks: Modern workloads are inherently chatty — calling third-party APIs, fetching images, pulling updates — and a single wildcard rule or misrouted path can silently open a wide-out-bound door.

The three classic traps: Binding rules to fast-rotting IP addresses, centralizing every decision through a single network appliance, and writing policies so complex that engineers route around them rather than update them.

Policy-as-code principles that scale: Encoding intent alongside syntax, anchoring policies to workload identity rather than IP, building developer-friendly allow-list on-ramps with scoped temporary exceptions, and keeping policy files readable and locally testable with tools like Open Policy Agent's Rego format.

The three-layer control architecture: How DNS policy validation, TLS client constraints, and route pinning through a service mesh or gateway must work in concert — and why a gap in any one of them undermines the other two.

Operational design for scale: Segmenting workloads by sensitivity and role, running a shared observability plane without creating a centralized bottleneck, and treating egress gateways as real products with owners, SLOs, and roadmaps. CyberAttack.ai's cloud security platform is built around exactly this kind of layered runtime visibility.

Allow-list hygiene and access lifetimes: Favoring DNS names over static IPs, scoping rules by data class and purpose, and enforcing expiration on every access grant so stale exceptions don't quietly accumulate into a museum of risk.

Metrics that actually matter: Shifting focus from rule counts to failed exfiltration attempts, exception approval time, wildcard reduction rates, and the proportion of traffic flowing through known egress points.
The episode closes with a four-question test for any egress architecture: Who is this workload? What is it allowed to reach? How do we know it followed the rules? Where is the proof? When those questions can be answered instantly — for any workload, at any time — egress control stops being a technical setting and becomes an organizational culture. For teams that want to build that culture with automated, continuous enforcement, CyberAttack.ai's compliance automation capabilities provide an audit-ready foundation across cloud environments.
More from the show: if this episode raised questions about how attackers exploit gaps in outbound controls before policies are in place, listen to Cloud Data Exfiltration: How Attackers Bypass Traditional Defenses for the threat-actor perspective.
CyberAttack.ai
10 min
September 03Cloud Data Exfiltration: How Attackers Bypass Traditional Defenses
Cloud environments were built for seamless access — and that's precisely what makes them a prime target. This episode of Cybersecurity examines the specific techniques attackers use to steal data from cloud infrastructure while evading the security tools most organizations rely on, drawing on this in-depth analysis of cloud data exfiltration tactics and defenses. The conversation cuts through vendor-speak to explain why perimeter-based thinking consistently fails in distributed cloud ecosystems — and what a more effective posture actually looks like.
The episode covers a wide range of attack vectors and defensive gaps, including:
Credential abuse and session hijacking — Attackers rarely "break in"; they log in using stolen credentials, phished tokens, or OAuth refresh tokens that persist long after initial compromise, blending into normal traffic that traditional tools can't distinguish from legitimate use.

API and OAuth vulnerabilities — Over-permissioned APIs, weak input validation, and long-lived refresh tokens give patient attackers persistent, low-noise access that most SIEMs under-log or miss entirely.

The dissolved perimeter — With ephemeral workloads and microservices communicating across namespaces, there is no meaningful network edge left to guard; data exits through allowed pathways that look indistinguishable from normal business traffic.

Misconfiguration and shadow IT — Exposed storage buckets and employee-provisioned, security-team-invisible cloud tools remain alarmingly common, each representing an unmonitored pathway into (and out of) the environment.

Serverless and container risks — Ephemeral serverless functions can execute a full data-extraction routine and vanish before logging captures them; Kubernetes misconfigurations — public dashboards, over-permissive service accounts — let attackers pivot across namespaces and erase their tracks.

Zero Trust and cloud-native detection — Genuinely implemented identity-based access control, continuous authentication, runtime behavioral analysis, and anomaly detection across cloud security workloads are positioned not as optional upgrades but as minimum requirements for catching exfiltration in progress.
A recurring theme throughout the episode is the danger of retrofitting legacy on-premises security tools onto cloud-native architectures. Static DLP rules, fixed heuristics, and perimeter firewalls were designed for a world that no longer exists — and attackers are fully aware of those blind spots. The shared responsibility model means cloud providers secure the infrastructure; everything above that layer is the organization's problem to solve. Robust attack surface monitoring that extends into APIs, serverless functions, container environments, and shadow IT infrastructure is what separates organizations that detect exfiltration early from those that discover it in a breach notification.
For more on related supply-chain and pipeline risks, check out the episode CI/CD Pipeline Hijacking: How Attackers Get In and How to Stop Them. When exfiltration is suspected, incident response sets how fast it is contained.
CyberAttack.ai
8 min
September 02CI/CD Pipeline Hijacking: How Attackers Get In and How to Stop Them
Modern software delivery pipelines are fast, automated, and increasingly in attackers' crosshairs. This episode of Cybersecurity examines CI/CD pipeline hijacking — an attack vector that lets adversaries ride trusted automation all the way to production, often without triggering a single traditional security alert. Drawing from this in-depth CyberAttack.ai breakdown on pipeline hijacking detection and prevention, the episode offers a stage-by-stage look at where pipelines break down and how defenders can close those gaps systematically.
Here's what the episode covers:
Why pipelines are high-value targets: Modern CI/CD environments hold API tokens, cloud credentials, signing certificates, and environment secrets — all connected directly to source code and production infrastructure. A single compromised link can hand an attacker a trusted, signed path to end users.

Where the vulnerabilities actually live: The episode maps four critical stages — source code management, build and test environments, artifact storage and dependency management, and the deployment layer — explaining how each can be exploited and why build systems are often far less instrumented than customer-facing assets.

Early detection signals to watch for: From unexpected OAuth app authorizations and off-hours SSH key additions in source control, to runners spawning interactive shells and large outbound transfers from build servers, the episode details concrete behavioral indicators that something has gone wrong — and when each signal should trigger immediate investigation.

Hardening controls at every pipeline stage: The episode walks through practical defenses including hardware-based MFA and signed commits at the source layer; ephemeral sandboxed build nodes and runtime secret injection for build infrastructure; SLSA provenance requirements and software bill of materials tooling for artifact management; and policy-as-code admission controllers plus eBPF-based sensors at deployment. Tools like Kyverno, OPA Gatekeeper, and Sigstore's cosign all get called out specifically.

The role of cloud security posture: Detecting drift between declared Infrastructure-as-Code state and what's actually running in cloud environments is highlighted as one of the most reliable signals that something changed without authorization — making continuous cloud security monitoring a natural complement to pipeline defenses.

Culture as a control: Technical measures alone aren't enough. The episode argues for a Secure DevOps mindset where developers threat-model pipeline features, security teams collaborate on post-mortems, and pipeline audit dashboards give every team visibility into who merged what and how it was built.
The central argument is simple and hard to argue with: a CI/CD pipeline is a security perimeter, and it deserves the same layered, rigorously monitored attention as a network edge or endpoint environment. The episode closes with a clear call to action — identify your highest-risk pipeline junctures, instrument what you currently can't see, and build the cross-functional culture that keeps pipeline security from falling through the cracks.
For more from the show, check out BIOS and UEFI Rootkits: What Infrastructure Teams Need to Know, which explores another deeply embedded and often overlooked attack surface. To spot exposed build infrastructure before attackers do, see attack surface monitoring.
CyberAttack.ai
9 min
September 01BIOS and UEFI Rootkits: What Infrastructure Teams Need to Know
Firmware is the first software to run on every machine in your fleet — and one of the last places most security programs look. This episode of Cybersecurity tackles one of the most technically daunting threats facing infrastructure teams today: BIOS and UEFI rootkits. Drawing on the CyberAttack.ai infrastructure-focused firmware rootkit primer, the episode translates low-level firmware concepts into actionable guidance for engineering managers, SREs, and security leaders — no chip-design expertise required.
The episode walks through why firmware-layer threats are categorically different from conventional malware, how modern UEFI architecture creates both protections and attack surface, and what a realistic defense and response program actually looks like. Key areas covered include:
Why firmware rootkits are so dangerous: Unlike OS-layer malware, they survive disk wipes, OS reinstalls, and reimaging — and can silently reinfect a clean operating system before security tools even start.

How attackers gain a foothold: Three primary vectors — supply chain and update abuse, exploitation of firmware interfaces such as System Management Mode and option ROM handlers, and physical access to hardware debug ports or configuration jumpers.

What implants do once installed: UEFI implants hook early boot services, patch kernel loaders in memory, target SMM for maximum privilege, or manipulate NVRAM variables — all while bypassing or disabling the security controls that come to life later in the boot sequence.

Detection through attestation: Capturing golden measurements on clean systems, using TPM-based Measured Boot, and continuously comparing hashes through remote attestation — rather than trusting a potentially compromised OS to self-report.

Hardening priorities: Properly configuring Secure Boot with current keys and no unnecessary fallback paths, enabling SPI flash write protections and Boot Guard, enforcing BIOS/UEFI admin passwords, and patching firmware from authenticated sources with staged validation in lab environments. Endpoint monitoring that extends into the firmware layer is essential to catching drift before it becomes a crisis.

Incident response sequence: Isolating the host, capturing firmware images via trusted external methods, comparing against golden measurements before taking any remediation action, and — if trust cannot be restored — retiring the hardware entirely. Teams managing complex environments can benefit from a structured incident response workflow that accounts for firmware-layer scenarios.
The episode closes with an organizational lens: tracking firmware versions as first-class inventory data, building procurement criteria around vendor transparency on boot protections, maintaining a small hardware lab capable of controlled flash extraction, and planning proactively for end-of-life devices that can quietly become persistent liabilities.
For more on supply chain and boot-integrity topics, check out the episode Binary Provenance and SBOM Verification in Practice. Firmware flaws belong in the patch queue too; see vulnerability management.
CyberAttack.ai
9 min
August 31Binary Provenance and SBOM Verification in Practice
Software supply chain attacks don't announce themselves — they hide in the gap between what teams assume about their artifacts and what those artifacts actually contain. This episode of Cybersecurity digs into the practical mechanics of binary provenance and SBOM verification, drawing on this in-depth guide to binary provenance and SBOM verification in practice from the CyberAttack.ai research team. If your organization ships, deploys, or depends on compiled software, the workflows covered here are directly applicable.
The episode covers the full arc — from what provenance actually means at a technical level, to where SBOM pipelines break down in the real world, to how leading teams are building continuous verification loops that extend from commit all the way to runtime. Key topics include:
What provenance really means: Treating a binary as an artifact with a verifiable passport — linking it to a specific source commit, build environment, compiler flags, and inputs — rather than a mystery object dropped into a pipeline.

Why cryptographic signatures are non-negotiable: Provenance metadata is only useful when it's tamper-evident; verification must be independent of the pipeline that produced the artifact, not dependent on trusting it.

SBOM depth vs. breadth: Top-level package lists create a false sense of security — transitive dependencies are where real damage tends to occur, and hashes of exact files matter far more than version names or ranges.

The verification workflow: Developer key checks, builder-identity attestation, deterministic rebuilds, SBOM-to-artifact hash comparisons, transparency log inclusion, and vulnerability cross-referencing — all automated so no one has to remember a magic command on a Friday afternoon.

Common failure modes: Hash drift from nondeterministic builds, ghost dependencies that bypass lockfiles, and proprietary blobs that resist hashing — plus concrete mitigations for each. Teams using vulnerability management tooling can tie SBOM-flagged components directly into remediation workflows.

Measuring progress: Lead indicators like artifact diagnosis time, exception rates, and the percentage of SBOM components without hashes — metrics that matter for audits and for teams chasing compliance frameworks like SOC 2, CMMC, or ISO 27001.
The episode closes with a look at where the field is heading: hardware roots of trust making signing keys more tamper-resistant, and runtime attestation systems that refuse to launch code that can't prove its own lineage. The takeaway isn't that supply chain security requires a grand transformation — it requires reliable habits baked into build and promotion pipelines from the start.
For more on the intersection of network-layer risk and software trust, check out the episode BGP Hijacking: How Internet Routing Gets Weaponized. SBOMs are increasingly expected from anyone selling software to government; see government contractor compliance.
CyberAttack.ai
10 min
August 30BGP Hijacking: How Internet Routing Gets Weaponized
Every time data moves across the internet, it follows a path determined by a protocol almost no one thinks about — the Border Gateway Protocol. BGP is the backbone of global routing, and it was built on trust rather than verification. This episode of Cybersecurity explores what happens when that trust gets exploited, drawing on this deep-dive on BGP hijacking and how routing gets weaponized to unpack one of the internet's most quietly dangerous attack surfaces.
Here's what the episode covers:
How BGP actually works: Internet service providers use BGP to announce which IP address blocks they're responsible for — and because routers are designed to trust those announcements, a false claim can redirect massive amounts of traffic with no immediate alarm.

Accidental vs. intentional hijacks: Many routing incidents are genuine misconfiguration errors, but state-sponsored actors and criminal organizations have deliberately weaponized BGP for espionage and financial fraud — and the "probably just a mistake" assumption provides dangerous cover.

Why no organization is too small to be a target: High-profile hijacks make headlines, but smaller networks carrying personal data, financial transactions, or operational traffic are equally viable targets.

The stealth factor: The most dangerous BGP hijacks are the silent ones — man-in-the-middle rerouting attacks designed to intercept and pass along traffic without triggering any outage, sometimes going undetected for weeks.

RPKI and route filtering as the core technical defenses: Resource Public Key Infrastructure lets operators cryptographically sign their route announcements, giving routers a way to verify legitimacy. Combined with disciplined route filtering and real-time attack surface monitoring, these layers significantly reduce hijack risk.

The right questions to ask your provider: Whether you manage your own network or rely on an ISP or managed security partner, knowing what to ask about RPKI adoption, route filtering, and anomaly detection is a practical starting point.
The broader takeaway is one that applies well beyond BGP: protocols built on implicit trust — without cryptographic verification — will eventually be abused. Understanding the mechanics of how an attack works, not just that it exists, is what separates reactive security from a genuinely defensible posture. Organizations looking to move in that direction can explore incident response capabilities designed to catch and contain threats before they escalate into major damage.
For more on threats hiding in the infrastructure layer, check out the episode Bare-Metal Backdoors: Detecting Persistent Firmware-Level Implants. For triaging routing alerts like these at scale, see the AI security analyst.
CyberAttack.ai
9 min

About CyberAttack.ai

From the publisher's feed

AI cybersecurity and risk management for teams that have to prove their posture, not just describe it. Vulnerability management, detection engineering, compliance frameworks, vendor and third-party risk, and how automation changes the work of a small security function.

Share CyberAttack.ai

Sign up to save your podcasts

CyberAttack.ai

CyberAttack.ai episodes

About CyberAttack.ai