Tag: cyber-threat-intelligence

  • They Didn’t Break In. They Logged In: The Credential-First Ransomware Playbook Rewriting Your Threat Model

    They Didn’t Break In. They Logged In: The Credential-First Ransomware Playbook Rewriting Your Threat Model

    7,655 ransomware victims in 12 months (based on leak site tracking). One organization every 71 minutes. The dominant attack vector is not a vulnerability: it’s a valid login.

    From March 2025 to March 2026, ransomware groups posted 7,655 victim claims. That is one new organization posted every 71 minutes, every hour of every day for an entire year. Fifty-three ransomware groups claimed US victims in January and February 2026 alone. Qilin alone claimed 1,179 victims across 74 countries, averaging 3.1 new victims every single day.

    These numbers are striking. What is more striking is how the attacks actually begin. Ransomware is no longer primarily a story about exploiting technical vulnerabilities. The dominant shift in 2026 is identity-first attack: attackers prioritize credential theft, session token hijacking, and federated access abuse to achieve initial access. They do not break in through a zero-day. They log in with a valid credential.

    This rewrite of the ransomware playbook has profound implications for threat models that are organized around perimeter defense and vulnerability management. If the attacker already has valid credentials, your firewall sees a legitimate login. Your SIEM records an authenticated session. Your EDR agent sees a credentialed user executing commands. The threat is inside the perimeter from the first moment, and it looks like a trusted user.

    This post maps how credential-first ransomware works in 2026, why the identity perimeter is now the last line of defense, and what detection controls actually catch these attacks before encryption begins.

    What Is Credential-First Ransomware?

    Credential-first ransomware is a ransomware attack methodology that prioritizes obtaining valid authentication credentials as the first phase of the attack chain, rather than exploiting a technical vulnerability for initial access. This includes phishing-based credential theft, session token hijacking (including AiTM techniques), dark web purchase of previously stolen credentials, and insider recruitment.

    Once inside with valid credentials, attackers move methodically: they discover the environment, elevate privileges, disable security tooling, destroy backups, and stage data for exfiltration before deploying encryption. The credential is the key. Everything else follows from having it.

    The 2026 Ransomware Landscape: Who Is Attacking

    The credential theft ransomware identity attack landscape in 2026 is characterized by a maturing ecosystem of specialized groups with distinct operating patterns.

    Qilin leads by volume with 1,179 claims across 74 countries in the past 12 months. Akira targets mid-market organizations in manufacturing and professional services. Clop specializes in large-scale data theft from enterprise networks. INC Ransom and Play focus on critical infrastructure and healthcare. DragonForce and Sinobi represent newer entrants with rapidly growing victim counts.

    Across these groups, several structural trends define 2026 operations: faster rebranding cycles when heat increases, cross-platform encryption capability that operates across Windows, Linux, and VMware ESXi simultaneously, and double extortion as the baseline: data exfiltration before encryption, with two separate leverage points for payment.

    Perhaps most concerning: ransomware groups are actively recruiting native English speakers to approach corporate insiders as recruitment targets. A BBC reporter was contacted in 2026 by a group attempting to recruit insiders to plant ransomware in exchange for a share of the ransom. The attack surface now includes your employees as potential threat vectors.

    The Credential-First Attack Chain

    Phase 1: Credential Acquisition

    Attackers acquire credentials through multiple channels operating in parallel. Phishing campaigns deliver credential-harvesting pages or info-stealers. Dark web credential markets sell previously stolen credentials from historical breaches. Session tokens are harvested through AiTM phishing proxies that bypass MFA. Federated identity vulnerabilities allow credential reuse across cloud environments.

    Nation-state actors using AI to forge synthetic identities and deepfake personas have also been observed successfully passing recruitment and verification processes, establishing insider positions in targeted organizations. The acquisition phase is patient and multi-channel.

    Phase 2: Persistent Access Establishment

    With valid credentials, the attacker establishes persistent access using legitimate mechanisms: creating new accounts, adding MFA methods to existing accounts, registering new devices for trusted access, and installing remote management tools that are indistinguishable from legitimate IT infrastructure.

    This phase is where dwell time accumulates. Attackers may maintain persistent access for weeks before proceeding, gathering intelligence on network topology, backup architecture, and security tooling.

    Phase 3: Privilege Escalation and Lateral Movement

    Using the persistent access, attackers escalate privileges by exploiting misconfigured access controls, over-privileged service accounts, and legacy systems that lack modern authentication requirements. Lateral movement uses legitimate tools: RDP, WMI, PowerShell, and network file shares — activities that are difficult to distinguish from normal IT operations without behavioral context.

    Phase 4: Defense Evasion and Backup Destruction

    Before encryption, attackers systematically disable or evade security controls: stopping EDR agents, clearing logs, disabling backup processes, and staging data exfiltration. Backup destruction is completed before ransomware deployment to remove the recovery option. This phase is the critical window for detection: the behavioral patterns of backup access and deletion, logging changes, and security tool manipulation are detectable anomalies that precede encryption.

    Phase 5: Encryption and Double Extortion

    With defenses disabled and backups destroyed, encryption is deployed. Simultaneously, the exfiltrated data creates a second extortion lever: pay or the data is published. In 2026, the encryption phase is often the first moment organizations realize an attack is underway: by then, the damage is largely done.

    What Happens When Teams Miss the Early Phases

    Ransomware groups have adapted to detection at the encryption phase: they simply rebuild with a different tool and re-enter. The organizations that successfully reduce breach impact are those that detect the attack during credential acquisition, persistence establishment, or the lateral movement phase — before backup destruction begins. Peris.ai’s platform reduces breach impact by 53% and cost by 47% in documented deployments: that reduction comes from early-phase detection, not post-encryption response.

    Why Traditional Threat Models Miss Credential-First Ransomware

    The credential-first ransomware playbook is not a new tactic: it is the maturation of an approach that has been growing in prevalence for years, driven by the increasing availability of stolen credentials, the effectiveness of session token hijacking, and the reality that most organizations have stronger perimeter defenses than identity security.

    The threat model that treats network perimeter defense as the primary control is the wrong threat model for 2026. Identity security, behavioral analytics that surface anomalous credential use, and automated response speed are the controls that matter. Peris.ai’s XDR, BrahmaFusion, and IRP give SOC teams the identity-layer visibility, early-phase detection, and automated response capability to catch ransomware attacks before they reach the encryption phase.

    Because in 2026, the most dangerous actor in your environment is not breaking in. They are already logged in. And the clock is running.

    Learn how Peris.ai’s agentic AI platform empowers security teams to detect and stop credential-first ransomware before backup destruction begins. Want more insights? Visit Peris.ai.

    Frequently Asked Questions

    What is credential-first ransomware?

    Credential-first ransomware prioritizes obtaining valid authentication credentials as the first phase of the attack chain, using credential theft, session token hijacking, or dark web credential purchases to gain access, rather than exploiting technical vulnerabilities.

    How many ransomware attacks happened in 2025-2026?

    Ransomware groups posted 7,655 victim claims from March 2025 to March 2026 (based on leak site tracking), representing one new organization every 71 minutes.

    Who is Qilin ransomware?

    Qilin is the most prolific ransomware group in the 12-month period ending March 2026, claiming 1,179 victims across 74 countries at an average rate of 3.1 victims per day.

    Why does MFA no longer fully protect against ransomware?

    AiTM phishing techniques proxy the authentication flow, capturing the session token after MFA completes. Attackers replay the token to gain authenticated access without ever having the user’s credentials or MFA device.

    How does Peris.ai detect credential-first ransomware attacks?

    Peris.ai’s XDR correlates identity signals across endpoint, network, cloud, and authentication layers to detect anomalous credential use in the early attack phases. BrahmaFusion executes automated response playbooks to contain compromise before lateral movement or backup destruction occurs.

  • Hidden Threats: How Malicious Browser Extensions Are Hijacking Your Banking Data

    Hidden Threats: How Malicious Browser Extensions Are Hijacking Your Banking Data

    Browser extensions have become essential productivity tools—but now, they’re also being exploited by cybercriminals as stealthy data-stealing weapons. In a rising campaign dubbed Operation Phantom Enigma, attackers are using malicious browser add-ons to steal banking credentials, login information, and more—all while going undetected by most traditional security tools.

    Originating in Brazil, this campaign has quickly evolved into a global threat, targeting both individuals and enterprises across regions, particularly in Southeast Asia and Eastern Europe.

    It Starts With One Email—and One Dangerous Click

    This cyberattack follows a familiar but effective path: social engineering.

    • A fake email lands in your inbox—disguised as a bank alert or invoice.
    • Attached is a malicious file—often .exe, .msi, or .zip.
    • With one click, stealth malware is installed, bypassing basic antivirus detection.

    That single moment of distraction opens the door to a long-term compromise.

    What Happens Behind the Scenes

    Once deployed, the malware silently begins its attack:

    • Modifies system settings to weaken defenses
    • Disables security alerts so users remain unaware
    • Enables persistence, relaunching automatically every startup

    But the real danger begins when a rogue browser extension is installed.

    The Rogue Browser Extension Threat

    Without your knowledge, a fake extension is added to your Chromium-based browser (Chrome, Edge, or Brave). These malicious extensions are engineered to:

    • ⌨️ Log keystrokes—capturing usernames, passwords, and sensitive form data
    • Exfiltrate banking credentials in real time
    • Send stolen data to attacker-controlled servers

    Worse still, these add-ons often impersonate legitimate tools—making them nearly impossible to spot without advanced monitoring.

    Why It Started in Brazil—But No One Is Safe

    Operation Phantom Enigma was initially focused on users of Warsaw, a Brazilian banking plugin. But the malware is modular and adaptable—capable of morphing into variants that can target new languages, platforms, and geographies.

    Threat intelligence reports reveal:

    • Over 70 organizations impacted
    • More than 722 downloads of malicious extensions before takedown
    • Expansion into Southeast Asia and Eastern Europe already underway

    5 Cyber Hygiene Practices to Stop Malicious Extensions

    Here’s how to protect your users and systems from browser-based threats:

    1. Review Installed Extensions

    Go through your browser regularly. Remove unused or suspicious add-ons. Treat extensions like apps—vet their origin and update status.

    2. Avoid Unverified File Attachments

    Be wary of any .exe, .zip, .msi, or .bat files, even if sent by someone familiar. Always confirm via a second communication channel.

    3. Use AI-Powered Endpoint Protection

    Legacy antivirus isn’t enough. Solutions like Peris.ai Endpoint & Network Security offer:

    • Real-time monitoring of browser activity
    • Detection of unauthorized extension installs
    • Behavior analytics that flag suspicious changes
    • Automated incident response powered by BrahmaIRP

    4. Enforce Extension Policies Company-Wide

    Implement browser policies via Group Policy Objects (GPO) or Mobile Device Management (MDM) to restrict installations to pre-approved extensions only.

    5. Prioritize Regional Threat Awareness

    If your organization operates in Latin America, Southeast Asia, or Eastern Europe, assume elevated risk and strengthen endpoint controls immediately.

    Why This Threat Is Harder to Detect

    These extensions look and behave like real tools. Many even contain legitimate functionality to avoid suspicion—until they silently harvest credentials and open backdoors into your systems.

    In other words: they don’t act like malware—until it’s too late.

    Peris.ai Helps You Detect the Undetectable

    At Peris.ai Cybersecurity, we specialize in protecting against stealthy, browser-based threats that bypass traditional defenses.

    With tools like:

    • BrahmaIRP – AI-powered incident response that automates threat detection
    • BrahmaFusion – Hyperautomation platform that orchestrates defense workflows

    You can identify, contain, and remediate these attacks before credentials are stolen or networks compromised.

    Final Thought: Don’t Let Convenience Become Your Weakest Link

    Browser extensions were designed to make your work easier—but today, attackers are using that convenience against you.

    Protect your credentials, protect your endpoints, and question every tool that asks for permissions.

    Ready to secure your team’s browsers? Explore Peris.ai Endpoint Defense

  • What Happens When Your Threat Intelligence Is Too Slow?

    What Happens When Your Threat Intelligence Is Too Slow?

    In today’s volatile threat landscape, speed isn’t just an advantage—it’s survival.

    Every second a threat goes undetected, your systems become more vulnerable. Every minute without context is an opportunity for attackers to move laterally, escalate privileges, and exfiltrate data. Yet, many organizations still rely on delayed, fragmented, or static threat intelligence (TI)—believing it’s “better than nothing.”

    The truth? Slow threat intelligence might be worse than none at all.

    This article will break down the real-world consequences of lagging threat intel, why legacy models fail to protect against modern threats, and how organizations can shift to real-time, contextualized threat intelligence—like what Peris.ai delivers through its INDRA CTI platform.

    The Promise of Threat Intelligence—And the Common Pitfalls

    What Threat Intelligence Should Do:

    • Detect emerging threats faster than they can act
    • Correlate internal signals with global threat data
    • Inform decision-making in SOC, IR, and risk management
    • Support automation in playbooks and response workflows

    What Often Goes Wrong:

    • Delayed updates: Threat feeds update every 12–24 hours—too slow for modern attacks.
    • Generic IOCs: Intelligence lacks relevance to your specific infrastructure or industry.
    • Siloed data: Fragmented across tools and vendors, making it hard to correlate.
    • No context: SOC teams receive alerts without insight into origin, intent, or priority.
    • Manual overload: Analysts drown in false positives, missing critical incidents.

    What It Costs When Threat Intelligence Is Too Slow

    Delayed Response = Greater Damage

    • On average, attackers dwell in a network for over 200 days before detection.
    • Slow threat correlation means incidents are discovered post-exfiltration or ransomware deployment.

    Financial Impact

    • Response costs increase by 35–60% when detection is delayed.
    • Downtime, reputational loss, breach fines, and legal fallout escalate exponentially.

    Missed Opportunities for Containment

    • Real-time threat intel could block C2 communication or isolate endpoints automatically.
    • Without it, malicious activity moves deeper into your environment—unnoticed.

    SOC Analyst Fatigue

    • Manual analysis of unprioritized IOCs drains resources and morale.
    • Burnout increases while security posture worsens.

    Loss of Stakeholder Confidence

    • Boards, partners, and clients expect proactive cyber defense.
    • Repeated incidents caused by missed signals erode trust.

    Why Legacy Threat Intel Approaches Don’t Cut It

    Disconnected from Internal Signals

    • Many organizations treat TI as an external feed—not part of their actual detection stack.
    • This creates a blind spot where context is lacking: “Is this IOC relevant to me?”

    Static, File-Based Feeds

    • Daily or hourly CSV/JSON updates are too slow for polymorphic or AI-powered malware.
    • Emerging threats mutate faster than old-school intel cycles can track.

    No Behavioral Insight

    • Signature-based intelligence doesn’t explain how threats behave, just that they exist.
    • Without behavior + intent, you can’t prioritize or predict lateral movement.

    No Integration with SOAR/XDR

    • Threat intel isn’t used to automate decision-making—just sits in a dashboard.

    Reactive, Not Proactive

    • Many teams act only after compromise—not to prevent it.

    The New Standard: Real-Time, Contextual Threat Intelligence

    Organizations need intelligence that’s:

    • Real-time: Updates in minutes or seconds, not hours or days
    • Contextualized: Mapped to your actual environment, assets, and industry
    • Behavioral: Includes TTPs, not just IOCs
    • Integrated: Feeds directly into SIEM, SOAR, XDR, and IR tools
    • Risk-prioritized: Not just “what’s out there,” but “what matters to you now”

    This is what Peris.ai’s INDRA CTI platform was built to deliver.

    INDRA CTI: Faster, Smarter Threat Intelligence from Peris.ai

    How INDRA Works:

    • Pulls from global, dark web, and regional feeds
    • Correlates against internal telemetry from endpoints, networks, and cloud
    • Uses AI-powered enrichment to contextualize risk
    • Feeds directly into Peris.ai‘s Brahma Fusion, XDR, and IRP
    • Maps threats to MITRE ATT&CK, TTP chains, and asset criticality

    Key Capabilities:

    • Real-time IOC updates
    • Threat actor profiling (APT groups, regional threats)
    • Predictive attack simulation
    • Integration with SIEM, SOAR, EDR, XDR
    • Industry-specific threat briefings

    Use Case: SaaS Startup Defense

    • INDRA detected a spear-phishing domain registered 6 hours before the campaign launched.
    • It auto-enriched the alert in XDR, triggering auto-block rules in email security.
    • Result: 0 compromised accounts, no incident response needed.

    Why Speed + Context = Cyber Resilience

    From Raw Data to Actionable Intelligence

    • You don’t need “more” threat intel—you need relevant intel, right now.

    Empowering Automation

    • Real-time intel allows systems like Brahma Fusion to take immediate action: isolate a host, kill a process, block a domain—without waiting on humans.

    Enhancing Detection & Response

    • With INDRA + Peris.ai’s IRP, threats are not only detected faster, they’re contained, remediated, and reported in a unified workflow.

    Supporting Compliance

    • Demonstrates proactive defense and rapid response for ISO 27001, SOC 2, and GDPR audits.

    What You Can Do Right Now

    Audit Your Current Threat Intelligence Sources

    • Are they real-time?
    • Are they tailored to your industry?
    • Are they being used to trigger action?

    Integrate TI into Detection & Response

    • Feed IOCs and TTPs into XDR, EDR, firewall, and SIEM workflows.
    • Use automation to correlate internal logs against threat intel in real time.

    Invest in a Contextual Threat Intelligence Platform

    • Not just a feed. A full system like INDRA that prioritizes, enriches, and automates.

    Train Your SOC to Ask Better Questions

    • “How does this threat affect us?”
    • “What is the attacker likely to do next?”
    • “What asset is at the highest risk right now?”

    Conclusion: Threats Move Fast. Your Intelligence Has to Move Faster.

    In cybersecurity, speed = defense. The longer your systems take to understand, contextualize, and respond to a threat, the greater your risk. Static or siloed threat intelligence has no place in today’s attack landscape.

    The solution isn’t just to collect more data—it’s to build an ecosystem where actionable intelligence flows seamlessly from detection to response.

    That’s what we built INDRA CTI for. To help organizations of all sizes—especially in Southeast Asia and the Middle East—stay ahead of fast-moving, AI-powered, financially motivated, and state-backed threats.

    Ready to accelerate your threat detection? Visit www.peris.ai to explore how INDRA CTI and our modular cybersecurity platform can protect your business—faster, smarter, and at scale.

  • CTI Without Context Is Just Noise — Meet Peris.ai Indra

    CTI Without Context Is Just Noise — Meet Peris.ai Indra

    Cyber Threat Intelligence (CTI) is often hailed as the cornerstone of proactive cyber defense. From IOC feeds and TTP mapping to actor profiling, CTI promises to deliver foresight and operational clarity. But in practice, most security teams find themselves overwhelmed—not empowered—by the volume and complexity of CTI.

    Why? Because most CTI is delivered without context.

    Without integration into detection workflows, alignment with business risk, or correlation with active threats, CTI becomes just another stream of data. For already overloaded SOC analysts and security teams, this isn’t just inefficient—it’s dangerous.

    This article explores the core challenges of ineffective CTI programs, the urgent need for contextual intelligence, and how Peris.ai Indra transforms raw threat data into actionable insight—driving faster decisions, smarter automation, and stronger security outcomes.

    The Problem: Intelligence Isn’t Actionable Without Context

    1. Information Overload

    Organizations often subscribe to multiple CTI feeds:

    • Commercial threat providers
    • Government or ISAC alerts
    • Open-source IOC lists

    The result? Tens of thousands of indicators flood into SIEMs and security dashboards daily—creating more confusion than clarity.

    2. Lack of Prioritization

    Most CTI feeds are not tailored to your business. They can’t:

    • Identify which assets are critical to your operations
    • Weigh threat relevance based on organizational risk
    • Filter out IOCs already covered by existing controls

    3. Disconnected Workflows

    CTI often lives in isolation:

    • Outside of SIEMs, SOAR platforms, and response tools
    • Unavailable to analysts when alerts hit
    • Unused in detection, triage, or remediation processes

    4. Static Threat Reports

    Threat briefs and PDF intel reports are:

    • Outdated by the time they’re read
    • Non-machine-readable, making automation impossible
    • Siloed from the tools where detection happens

    5. No Feedback Loops

    Even when CTI is used, most platforms fail to:

    • Track how intelligence is applied
    • Update feeds based on SOC feedback or evolving threats
    • Adapt scoring based on internal telemetry

    Consequences of CTI Without Context

    Missed Threats

    • High-fidelity IOCs are ignored due to alert fatigue
    • Lack of correlation causes adversary campaigns to go unnoticed

    Wasted Resources

    • Analysts spend hours triaging irrelevant data
    • Security platforms process massive feeds that add little value

    Slower Response Times

    • Without clear attribution or context, IR teams struggle to reconstruct timelines
    • Remediation steps become reactive and ambiguous

    Loss of Trust in Threat Intel

    • SOC teams start to ignore CTI feeds
    • Leadership questions the ROI of threat intelligence investment

    What Context-Driven CTI Should Look Like

    Effective CTI must be:

    • Relevant to your industry, region, and infrastructure
    • Timely, delivered in sync with alert triage and investigations
    • Correlated with internal telemetry and user behavior
    • Actionable, embedded in response workflows and decision points

    Introducing Peris.ai Indra: Contextual CTI That Powers Decisions

    Peris.ai Indra is not just another feed. It’s an intelligence correlation engine that transforms scattered data into decision-ready insight—right where it’s needed, when it’s needed.

    Core Capabilities of Indra

    1. Threat Actor and Campaign Correlation

    • Maps IOCs to known threat actor profiles
    • Tracks evolving TTPs across industries and geographies
    • Supports attribution, proactive blocking, and red team simulation

    2. Real-Time IOC Enrichment

    • Integrates directly into SIEMs, EDRs, and SOAR platforms
    • Enriches alerts with metadata: kill chain stage, source, frequency, risk level
    • Flags prevalence and first seen/last seen timestamps

    3. Confidence Scoring and Relevance Filtering

    • Uses contextual scoring based on your industry, asset class, and telemetry
    • Filters known false positives or low-impact indicators automatically

    4. Alert and Playbook Integration

    • Embeds threat intelligence directly into response workflows
    • Enhances behavior-based detections with external intelligence
    • Prioritizes alerts tied to active adversary campaigns

    5. Analyst-Centric Feedback Loops

    • Captures analyst interactions to improve scoring accuracy
    • Allows for analyst-sourced IOCs and in-field threat sightings
    • Continuously improves through usage-based learning

    Real-World Use Case: Stopping a Targeted Phishing Campaign

    Background: A regional financial services provider received a medium-severity alert for anomalous login behavior.

    Indra’s Role:

    • Correlated the login source with a Southeast Asia phishing campaign targeting digital banking platforms
    • Elevated the alert severity based on active campaign data
    • Delivered YARA rules and watchlists to endpoint protection systems
    • Triggered automated workflows: locked the user account, alerted the IR team, and launched forensic logging

    Outcome:

    • Contained the threat in under 15 minutes
    • Prevented potential credential compromise and downstream financial fraud

    Pain Points Solved by Indra

    Pain Point: Alert fatigue

    • Indra suppresses irrelevant IOCs (Indicators of Compromise) and scores relevance per asset to reduce noise.

    Pain Point: Workflow disconnects

    • Indra feeds Cyber Threat Intelligence (CTI) directly into alerts and automated response workflows for seamless integration.

    Pain Point: Poor prioritization

    • Indra aligns threat indicators with active attack campaigns and threat actor profiles, enabling better prioritization.

    Pain Point: Manual research burden

    • Indra enriches alerts instantly with information about threat actors, their tactics, and contextual details.

    Pain Point: Static threat feeds

    • Indra pulls real-time updates from OSINT sources, the dark web, and analyst feedback to keep intelligence current.

    Integration-First by Design

    Indra was built to enhance—not replace—your existing stack:

    • SIEMs (Splunk, Sentinel, Elastic) → Contextual alert enrichment
    • EDR/NDR Platforms → Correlated threat actor TTP profiles
    • SOAR Playbooks → Triggered actions based on matched campaigns
    • Ticketing Systems → Pre-populated context and linked evidence

    Intelligence Sources Used by Indra

    • Commercial CTI partnerships
    • Public threat feeds (CISA, CERTs, industry ISACs)
    • Dark web forums and breach markets
    • OSINT from Telegram, GitHub, forums, and paste sites
    • Malware sandbox analysis
    • Red team and deception telemetry from Peris.ai engagements

    CTI as a Strategic Asset

    When done right, CTI does more than inform detection. It adds value across:

    • CISO Dashboards: Aligns threat landscape with enterprise risk exposure
    • Board Reporting: Demonstrates actionable readiness and attacker awareness
    • Compliance: Shows evidence of control decisions based on real threat data
    • Red Teaming: Enables simulations of live adversary behavior

    Getting Started with Indra

    1. Connect Telemetry Sources: Start with SIEM and EDR data ingestion
    2. Customize Threat Filters: Prioritize intel based on geography, sector, and critical assets
    3. Push Context to Analysts: Display enriched intel directly in alert consoles
    4. Map to Existing Playbooks: Define auto-response triggers for critical threat actor behavior
    5. Train Your Teams: Embed CTI in threat hunting, incident response, and vulnerability prioritization

    Metrics That Matter

    Organizations using Indra report:

    • 40–60% reduction in MTTD through prioritized detection
    • Up to 75% fewer false-positive investigations
    • Stronger SOC confidence and less burnout
    • Improved executive trust in cyber risk reporting

    Conclusion: Make Intelligence Work for You

    Most security teams don’t suffer from a lack of data—they suffer from a lack of context.

    Peris.ai Indra helps you turn threat intelligence into threat understanding. By connecting external campaigns to internal risk, enriching alerts, and feeding decisions across the stack, Indra makes CTI a real-time force multiplier—not a burden.

    Intelligence is only powerful when it’s usable. With Indra, context becomes your strongest signal.

    Learn more at https://peris.ai/