Blog
/
/
August 9, 2023

Improve Security with Attack Path Modeling

Learn how to prioritize vulnerabilities effectively with attack path modeling. Learn from Darktrace experts and stay ahead of cyber threats.
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Max Heinemeyer
Global Field CISO
Written by
Adam Stevens
Senior Director of Product, Cloud | Darktrace
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
09
Aug 2023

TLDR: There are too many technical vulnerabilities and there is too little organizational context for IT teams to patch effectively. Attack path modelling provides the organizational context, allowing security teams to prioritize vulnerabilities. The result is a system where CVEs can be parsed in, organizational context added, and attack paths considered, ultimately providing a prioritized list of vulnerabilities that need to be patched.

Figure 1: The Darktrace user interface presents risk-prioritized vulnerabilities


This blog post explains how Darktrace addresses the challenge of vulnerability prioritization. Most of the industry focusses on understanding the technical impact of vulnerabilities globally (‘How could this CVE generally be exploited? Is it difficult to exploit? Are there pre-requisites to exploitation? …’), without taking local context of a vulnerability into account. We’ll discuss here how we create that local context through attack path modelling and map it to technical vulnerability information. The result is a stunningly powerful way to prioritize vulnerabilities.

We will explore:

1)    The challenge and traditional approach to vulnerability prioritization
2)    Creating local context through machine learning and attack path modelling
3)    Examining the result – contextualized, vulnerability prioritization

The Challenge

Anyone dealing with Threat and Vulnerability Management (TVM) knows this situation:

You have a vulnerability scanning report with dozens or hundreds of pages. There is a long list of ‘critical’ vulnerabilities. How do you start prioritizing these vulnerabilities, assuming your goal is reducing the most risk?

Sometimes the challenge is even more specific – you might have 100 servers with the same critical vulnerability present (e.g. MoveIT). But which one should you patch first, as all of those have the same technical vulnerability priority (‘critical’)? Which one will achieve the biggest risk reduction (critical asset e.g.)? Which one will be almost meaningless to patch (asset with no business impact e.g.) and thus just a time-sink for the patch and IT team?

There have been recent improvements upon flat CVE-scoring for vulnerability prioritization by adding threat-intelligence about exploitability of vulnerabilities into the mix. This is great, examples of that additional information are Exploit Prediction Scoring System (EPSS) and Known Exploited Vulnerabilities Catalogue (KEV).

Figure 2: The idea behind EPSS – focus on actually exploited CVEs. (diagram taken from https://www.first.org/epss/model)

With CVE and CVSS scores we have the theoretical technical impact of vulnerabilities, and with EPSS and KEV we have information about the likelihood of exploitation of vulnerabilities. That’s a step forward, but still doesn’t give us any local context. Now we know even more about the global and generic technical risk of a vulnerability, but we still lack the local impact on the organization.

Let’s add that missing link via machine learning and attack path modelling.

Adding Attack Path Modelling for Local Context

To prioritize technical vulnerabilities, we need to know as much as we can about the asset on which the vulnerability is present in the context of the local organization. Is it a crown jewel? Is it a choke point? Does it sit on a critical attack path? Is it a dead end, never used and has no business relevance? Does it have organizational priority? Is the asset used by VIP users, as part of a core business or IT process? Does it share identities with elevated credentials? Is the human user on the device susceptible to social engineering?

Those are just a few typical questions when trying to establish local context of an asset. Knowing more about the threat landscape, exploitability, or technical information of a CVE won’t help answer any of the above questions. Gathering, evaluating, maintaining, and using this local context for vulnerability prioritization is the hard part. This local context often resides informally in the head of the TVM or IT team member, having been assembled by having been at the organization for a long time, ‘knowing’ systems, applications and identities in question and talking to asset and application owners if time permits. This does unfortunately not scale, is time-consuming and heavily dependent on individuals.

Understanding all attack paths for an organization provides this local context programmatically.

We discover those attack paths, and these are bespoke for each organization through Darktrace PREVENT, using the following method (simplified):

1)    Build an adaptive model of the local business. Collect, combine, and analyze (using machine learning and non-machine learning techniques) data from various data domains:

a.     Network, Cloud, IT, and OT data (network-based attack paths, communication patterns, peer-groups, choke-points, …). Natively collected by Darktrace technology.

b.     Email data (social engineering attack paths, phishing susceptibility, external exposure, security awareness level, …). Natively collected by Darktrace technology.

c.     Identity data (account privileges, account groups, access levels, shared permissions, …). Collected via various integrations, e.g. Active Directory.

d.     Attack surface data (internet-facing exposure, high-impact vulnerabilities, …). Natively collected by Darktrace technology.

e.     SaaS information (further identity context). Natively collected by Darktrace

f.      Vulnerability information (CVEs, CVSS, EPSS, KEV, …). Collected via integrations, e.g. Vulnerability Scanners or Endpoint products.

Figure 3: Darktrace PREVENT revealing each stage of an attack path

2)    Understand what ‘crown jewels’ are and how to get to them. Calculate entity importance (user, technical asset), exposure levels, potential damage levels (blast radius) weakness levels, and other scores to identify most important entities and their relationships to each other (‘crown jewels’).

Various forms of machine learning and non-machine learning techniques are used to achieve this. Further details on some of the exact methods can be found here. The result is a holistic, adaptive and dynamic model of the organization that shows most important entities and how to get to them across various data domains.

The combination of local context and technical context, around the severity and likelihood of exploitation, creates the Darktrace Vulnerability Score. This enables effective risk-based prioritisation of CVE patching.

Figure 4: List of devices with the highest damage potential in the organization - local context

3)    Map the attack path model of the organization to common cyber domain knowledge. We can then combine things like MITRE ATT&CK techniques with those identified connectivity patterns and attack paths – making it easy to understand which techniques, tools and procedures (TTPs) can be used to move through the organization, and how difficult it is to exploit each TTP.

Figure 5: An example attack path with associated MITRE techniques and difficulty scores for each TTP

We can now easily start prioritizing CVE patching based on actual, organizational risk and local context.

Bringing It All Together

Finally, we overlay the attack paths calculated by Darktrace with the CVEs collected from a vulnerability scanner or EDR. This can either happen as a native integration in Darktrace PREVENT, if we are already ingesting CVE data from another solution, or via CSV upload.

Figure 6: Darktrace's global CVE prioritization in action.

But you can also go further than just looking at the CVE that delivers the biggest risk reduction globally in your organization if it is patched. You can also look only at certain group of vulnerabilities, or a sub-set of devices to understand where to patch first in this reduced scope:

Figure 7: An example of the information Darktrace reveals around a CVE

This also provides the TVM team clear justification for the patch and infrastructure teams on why these vulnerabilities should be prioritized and what the positive impact will be on risk reduction.

Attack path modelling can be utilized for various other use cases, such as threat modelling and improving SOC efficiency. We’ll explore those in more depth at a later stage.

Want to explore more on using machine learning for vulnerability prioritization? Want to test it on your own data, for free? Arrange a demo today.

Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Max Heinemeyer
Global Field CISO
Written by
Adam Stevens
Senior Director of Product, Cloud | Darktrace

More in this series

No items found.

Blog

/

/

September 23, 2025

It’s Time to Rethink Cloud Investigations

cloud investigationsDefault blog imageDefault blog image

Cloud Breaches Are Surging

Cloud adoption has revolutionized how businesses operate, offering speed, scalability, and flexibility. But for security teams, this transformation has introduced a new set of challenges, especially when it comes to incident response (IR) and forensic investigations.

Cloud-related breaches are skyrocketing – 82% of breaches now involve cloud-stored data (IBM Cost of a Data Breach, 2023). Yet incidents often go unnoticed for days: according to a 2025 report by Cybersecurity Insiders, of the 65% of organizations experienced a cloud-related incident in the past year, only 9% detected it within the first hour, and 62% took more than 24 hours to remediate it (Cybersecurity Insiders, Cloud Security Report 2025).

Despite the shift to cloud, many investigation practices remain rooted in legacy on-prem approaches. According to a recent report, 65% of organizations spend approximately 3-5 days longer when investigating an incident in the cloud vs. on premises.

Cloud investigations must evolve, or risk falling behind attackers who are already exploiting the cloud’s speed and complexity.

4 Reasons Cloud Investigations Are Broken

The cloud’s dynamic nature – with its ephemeral workloads and distributed architecture – has outpaced traditional incident response methods. What worked in static, on-prem environments simply doesn’t translate.

Here’s why:

  1. Ephemeral workloads
    Containers and serverless functions can spin up and vanish in minutes. Attackers know this as well – they’re exploiting short-lived assets for “hit-and-run” attacks, leaving almost no forensic footprint. If you’re relying on scheduled scans or manual evidence collection, you’re already too late.
  2. Fragmented tooling
    Each cloud provider has its own logs, APIs, and investigation workflows. In addition, not all logs are enabled by default, cloud providers typically limit the scope of their logs (both in terms of what data they collect and how long they retain it), and some logs are only available through undocumented APIs. This creates siloed views of attacker activity, making it difficult to piece together a coherent timeline. Now layer in SaaS apps, Kubernetes clusters, and shadow IT — suddenly you’re stitching together 20+ tools just to find out what happened. Analysts call it the ‘swivel-chair Olympics,’ and it’s burning hours they don’t have.
  3. SOC overload
    Analysts spend the bulk of their time manually gathering evidence and correlating logs rather than responding to threats. This slows down investigations and increases burnout. SOC teams are drowning in noise; they receive thousands of alerts a day, the majority of which never get touched. False positives eat hundreds of hours a month, and consequently burnout is rife.  
  4. Cost of delay
    The longer an investigation takes, the higher its cost. Breaches contained in under 200 days save an average of over $1M compared to those that linger (IBM Cost of a Data Breach 2025).

These challenges create a dangerous gap for threat actors to exploit. By the time evidence is collected, attackers may have already accessed or exfiltrated data, or entrenched themselves deeper into your environment.

What’s Needed: A New Approach to Cloud Investigations

It’s time to ditch the manual, reactive grind and embrace investigations that are automated, proactive, and built for the world you actually defend. Here’s what the next generation of cloud forensics must deliver:

  • Automated evidence acquisition
    Capture forensic-level data the moment a threat is detected and before assets disappear.
  • Unified multi-cloud visibility
    Stitch together logs, timelines, and context across AWS, Azure, GCP, and hybrid environments into a single unified view of the investigation.
  • Accelerated investigation workflows
    Reduce time-to-insight from hours or days to minutes with automated analysis of forensic data, enabling faster containment and recovery.
  • Empowered SOC teams
    Fully contextualised data and collaboration workflows between teams in the SOC ensure seamless handover, freeing up analysts from manual collection tasks so they can focus on what matters: analysis and response.

Attackers are already leveraging the cloud’s agility. Defenders must do the same — adopting solutions that match the speed and scale of modern infrastructure.

Cloud Changed Everything. It’s Time to Change Investigations.  

The cloud fundamentally reshaped how businesses operate. It’s time for security teams to rethink how they investigate threats.

Forensics can no longer be slow, manual, and reactive. It must be instant, automated, and cloud-first — designed to meet the demands of ephemeral infrastructure and multi-cloud complexity.

The future of incident response isn’t just faster. It’s smarter, more scalable, and built for the environments we defend today, not those of ten years ago.  

On October 9th, Darktrace is revealing the next big thing in cloud security. Don’t miss it – sign up for the webinar.

darktrace live event launch
Continue reading
About the author
Kellie Regan
Director, Product Marketing - Cloud Security

Blog

/

/

September 22, 2025

Understanding the Canadian Critical Cyber Systems Protection Act

Canadian critical cyber systems protection actDefault blog imageDefault blog image

Introduction: The Canadian Critical Cyber Systems Protection Act

On 18 June 2025, the Canadian federal Government introduced Bill C-8 which, if adopted following completion of the legislative process, will enact the Critical Cyber Systems Protection Act (CCSPA) and give Canada its first federal, cross-sector and legally binding cybersecurity regime for designated critical infrastructure providers. As of August 2025, the Bill has completed first reading and stands at second reading in the Canadian House of Commons.

Political context

The measure revives most of the stalled 2022 Bill C-26 “An Act Respecting Cyber Security” which “died on Paper” when Parliament was prorogued in January 2025, in the wake of former Prime Minister Justin Trudeau’s resignation.

The new government, led by Mark Carney since March 2025, has re-tabled the package with the same two-part structure: (1) amendments to the Telecommunications Act that enable security directions to telecoms; and (2) a new CCSPA setting out mandatory cybersecurity duties for designated operators. This blog focuses on the latter.

If enacted, Canada will join fellow Five Eyes partners such as the United Kingdom and Australia, which already impose statutory cyber-security duties on operators of critical national infrastructure.

The case for new cybersecurity legislation in Canada

The Canadian cyber threat landscape has expanded. The country's national cyber authority, the Canadian Centre for Cybersecurity (Cyber Centre), recently assessed that the number of cyber incidents has “sharply increased” in the last two years, as has the severity of those incidents, with essential services providers among the targets. Likewise, in its 2025-2026 National Cyber Threat Assessment, the Cyber Centre warned that AI technologies are “amplifying cyberspace threats” by lowering barriers to entry, improving the speed and sophistication of social-engineering attacks and enabling more precise operations.

This context mirrors what we are seeing globally: adversaries, including state actors, are taking advantage of the availability and sophistication of AI tools, which they have leverage to amplify the effectiveness of their operations. In this increasingly complex landscape, regulation must keep pace and evolve in step with the risk.

What the Canadian Critical Cyber Systems Protection Act aims to achieve

  • If enacted, the CCSPA will apply to operators in federally regulated critical infrastructure sectors which are vital to national security and public safety, as further defined in “Scope” below (the “Regulated Entities”), to adopt and comply with a minimum standard of cybersecurity duties (further described below)  which align with those its Five Eyes counterparts are already adhering to.

Who does the CCSPA apply to

The CCSPA would apply to designated operators that deliver services or systems within federal jurisdiction in the following priority areas:

  • telecommunications services
  • interprovincial or international pipeline and power line systems, nuclear energy systems, transportation systems
  • banking and clearing  
  • settlement systems

The CCSPA would also grant the Governor in Council (Federal Cabinet) with powers to add or remove entities in scope via regulation.

Scope of the CCSPA

The CCSPA introduces two key instruments:

First, it strengthens cyber threat information sharing between responsible ministers, sector regulators, and the Communications Security Establishment (through the Cyber Centre).

Second, it empowers the Governor in Council (GIC) to issue Cyber Security Directions (CSDs) - binding orders requiring a designated operator to implement specified measures to protect a critical cyber system within defined timeframes.

CSDs may be tailored to an individual operator or applied to a class of operators and can address technology, process, or supplier risks. To safeguard security and commercial confidentiality, the CCSPA restricts disclosure of the existence or content of a CSD except as necessary to carry it out.

Locating decision-making with the GIC ensures that CSDs are made with a cross-government view that weighs national security, economic priorities and international agreement.

New obligations for designated providers

The CCSPA would impose key cybersecurity compliance and obligations on designated providers. As it stands, this includes:

  1. Establishing and maintaining cybersecurity programs: these will need to be comprehensive, proportionate and developed proactively. Once implemented, they will need to be continuously reviewed
  2. Mitigating supply chain risks: Regulated Entities will be required to assess their third-party products and services by conducting a supply chain analysis, and take active steps to mitigate any identified risks
  3. Reporting incidents:  Regulated Entities will need to be more transparent with their reporting, by making the Communications Security Establishment (CSE) aware of any incident which has, or could potentially have, an impact on a critical system. The reports must be made within specific timelines, but in any event within no more than 72 hours;
  4. Compliance with cybersecurity directions:  the government will, under the CCSPA, have the authority to issue cybersecurity directives in an effort to remain responsive to emerging threats, which Regulated Entities will be required to follow once issued
  5. Record keeping: this shouldn’t be a surprise to many of those Regulated Entities which fall in scope, which are already likely to be subject to record keeping requirements. Regulated Entities should expect to be maintaining records and conducting audits of their systems and processes against the requirements of the CCSPA

It should be noted, however, that this may be subject to change, so Regulated Entities should keep an eye on the progress of the Bill as it makes its way through parliament.

Enforcement of the Act would be carried out by sector-specific regulators identified in the Act such as the Office of the Superintendent of Financial Institutions, Minister of Transport, Canada Energy Regulator, Canadian Nuclear Safety Commission and the Ministry of Industry.

What are the penalties for CCSPA non-compliance?

When assessing the penalties associated with non-compliance with the requirements of the CCSPA, it is clear that such non-compliance will be taken seriously, and the severity of the penalties follows the trend of those applied by the European Union to key pieces of EU legislation. The “administrative monetary penalties” (AMPs) set by regulation could see fines being applied of up to C$1 million for individuals and up to C$15 million for organizations.

Continue reading
About the author
The Darktrace Community
Your data. Our AI.
Elevate your network security with Darktrace AI