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LevelBlue TTP Briefing Q3 2026: Trusted Access Fuels Data Theft

Explore the latest tactics, techniques, and procedures (TTPs) our incident response (IR) experts are actively facing in the quarterly TTP Briefing, a report built on frontline threat intelligence from our global incident response investigations across LevelBlue during Q3 2026.

 

A Unified View of the Threat Landscape

This TTP Briefing is based on threat intelligence derived directly from LevelBlue incident response engagements worldwide over the past quarter. These engagements are technology-agnostic, providing a clear view into the real-world tactics, techniques, and procedures adversaries are using today.

The latest edition also incorporates threat intelligence from LevelBlue SpiderLabs, which broadens the dataset behind our findings.

 

Trusted Access Fuels Data Theft

The theme of the quarter: trusted access fuels data theft. Attackers didn’t need to break in so much as log in. Session tokens captured by phishing kits, OAuth apps users consented to, VPN appliances that accepted forged authentication, and remote management tools that look like routine IT all gave threat actors a foothold that looked legitimate from the inside. Once there, they went after data. We observed data exfiltration appearing in 83% of intrusion cases, while encryption is at 67%. In Q2, both were 77%. Non-ransomware network intrusions were the second most common incident type, and for the first time, exfiltration overtook viewing or accessing files as the most common outcome when data was at risk.

This briefing breaks down what our IR teams saw this quarter: who was targeted, how attackers got in, what they did once inside, and how fast they moved. Each section closes with guidance defenders can act on now.

Across our investigations this quarter, four themes stood out: attackers are diversifying initial access methods, identity has become a primary battleground, data theft is increasingly replacing encryption as the preferred source of leverage, and both attackers and defenders are moving faster than ever.

For additional insights, join our IR experts on November 10 at 11:00am ET or November 12 at 11:00am GMT for live webinars where they will explore our findings in more detail. Come armed with questions and walk away with actionable intelligence, detection priorities, and recommendations to strengthen your defenses.

Let’s explore a few key findings:

 

Most Common Threat Types

incident types qq
Figure 1. Most common threat types.

  • BECs continued to be the most common threat incident type, accounting for 32% of incidents.
  • Network intrusions without ransomware held steady as the 2nd most common incident type at 22%. This is largely due to threat actors focusing on exfiltration and extortion, rather than encryption.
  • Ransomware was the 3rd most common incident type, accounting for 20% of incidents this quarter.

Detection built around encryption events will miss a growing share of intrusions. Watch for large outbound transfers, unusual archive creation, and new cloud storage destinations.

 

Data Exfiltration Becomes the Focus for Attackers

Exfiltration/extortion-only attacks were the fastest-growing category in Q3, with attackers stealing data and threatening to publish it without deploying ransomware. Attacks that combine encryption with exfiltration remain the most common, but their share has fallen each quarter. This suggests encryption is no longer a given in ransomware cases, and the leverage increasingly comes from the stolen data itself.

intrusions qq
Figure 2. Intrusions.

The tools observed during investigations reinforce this trend. Utilities such as rclone, MegaSync, WinSCP, 7-Zip, and WinRAR continue to play an important role in attacker workflows, helping collect, package, and transfer sensitive information outside the organization.

Protecting systems remains essential, but organizations must also understand where their most sensitive information resides, who has access to it, and how they will detect abnormal movement or exfiltration activity before data leaves the environment.

Initial Intrusion Vector (How Are They Getting In?)

iiv qq
Figure 3. Initial intrusion vectors.

Phishing remained the top initial intrusion vector in Q3 at 42%, down from 65% in Q2. External remote services (RDP, VPN) and exploited vulnerabilities tied for second at 14% each. Together, those two internet-facing routes now account for more than a quarter of initial access.

 

Identity Is the Thread Through the Intrusion

  • Valid-account abuse has grown in each quarter. It is still a small share of initial access, but the direction is clear.
  • Social engineering often ends in stolen identities. Phishing/social engineering remains the most common way in, and that category includes vishing and help-desk impersonation. Many of those cases result in stolen credentials or tokens, so identity likely plays a larger role than the valid-accounts bar alone shows.

 

Most Commonly Observed CVEs – Q3

These are the vulnerabilities our incident response teams saw actively exploited in real incidents this quarter, which makes them a sharper patching priority list than any CVSS score.

CVE-2026-0257

PAN-OS Global Protect

CVE-2026-25639

Axios TypeError

CVE-2026-72898

Metabase

CVE-2025-13407

Gravity Forms WordPress plugin

CVE-2024-40762

SonicWall SonicOS SSLVPN

CVE-2024-40766

SonicWall SonicOS SSLVPN

CVE-2024-53704

SonicWall SonicOS SSLVPN

CVE-2024-53705

SonicWall SonicOS SSRF

CVE-2022-26923

Active Directory Domain Services

Inside the CVE Numbers:

Inventory internet-facing business applications, not just network appliances. If it touches sensitive data and faces the internet, it belongs on the emergency patch list.

 

Exploitation Is Back, and Initial Access Diversifies

While social engineering remains a top concern, internet-facing flaws have increased as an initial access route, with CVEs and external remote services both rising in Q3. Attackers are using a wider mix of entry points, including vulnerabilities like Metabase.

A look at Metabase - CVE-2026-72898

A vulnerability was discovered earlier this quarter in Metabase, an open-source business intelligence and data visualization platform. Identified as CVE-2026-72898, this vulnerability allows for unauthenticated SQL Injection that could lead to remote code execution with a cvss score of 10. If exploited, this vulnerability could allow a threat actor to hijack an account and gain admin access to the connected Metabase instance. From there, we observed threat actors creating new admin accounts, and leveraging the AI engines to gain access to 3rd parties connected to Metabase, and exfiltrating data from there and extorting the victim. This vulnerability allowed for a fully self-contained intrusion path from initial access through end goal.

 

MFA Bypass

mfa bypass qq
Figure 4. MFA bypass.

MFA is close to universal among the organizations we respond to, yet it no longer stops business email compromise attacks. In Q3, threat actors bypassed MFA in 79% of BEC incidents where it was enabled.

Although MFA remains widely deployed, attackers are increasingly sidestepping it through vishing, convincing victims to enroll an attacker-controlled device on their account. Because the victim approves the registration, the access appears legitimate, reflecting a shift from token interception to abuse of trusted device enrollment. Additionally, threat actors are relying more on machine identity and token abuse, rather than a normal user account attack, which does not involve bypassing MFA, contributing to the dip in our bypass stat.

Because attackers increasingly rely on valid tokens rather than defeating the prompt, pair MFA with continuous session-token monitoring, short token lifetimes, and conditional-access policies that flag anomalous token use.

The lesson is clear: identity security cannot be a standalone initiative. Organizations should pair phishing-resistant MFA with stronger monitoring of enrollment activity, conditional access controls, and greater visibility into account misuse across cloud and on-premises environments.

 

Most Targeted Industries and Company Sizes

Industires qq
Figure 5. Most targeted industries.

Targeted industries saw a shift in Q3. Financial services, which had been the top impacted sector for the last few quarters, dropped to #4, accounting for only 11% of incidents in Q3, down from 28%. Technology & Software surged to the top spot, accounting for 14% in Q3, up from 5% in Q2, and 3% in Q1. Healthcare and Manufacturing tied for the 2nd spot at 13%. This shift demonstrates that no industry is off limits to threat actors, and every sector should focus on cyber resilience.

Technology & Software spike: We observed an increase in compromised custom software and applications via exposed API keys, a trend that became more common in Q3 as threat actors used AI to hunt for exposed keys as an entry point into custom technologies. Because API keys are often long-lived, over-permissioned, and bypass MFA, a single exposed key can give direct access to sensitive data and connected systems. That reach, which can extend to a provider’s customers, makes the sector an attractive target.

Organizations with revenue between $1M–$100M accounted for the largest share of incidents in Q3, reinforcing that threat actors increasingly view mid-market companies as high-value, lower-resistance targets.

 

Tactics Across the Intrusion Path

undefined-Oct-27-2026-05-19-09-9456-PM
Figure 6. Trends across the intrusion path.

The TTP Briefing provides data across the five stages of the intrusion path, from initial access to persistence and escalation techniques, to exfiltration and monetization tactics. Noteworthy findings include:

  • Back door/remote access tools remain the most common tool type leveraged to gain persistence, using tools like ScreenConnect and MeshAgent to maintain access.
  • Credential stealers, like mimikatz and DCSync, continue to be commonly used to escalate privileges, as identity compromise remains a top concern.
  • During the data at risk stage of the intrusion path, files were most often exfiltrated, surpassing viewed/accessed for the first time, highlighting that threat actors are focusing heavily on data exfiltration.

 

A Look Into Dwell Time

dwell time qq
Figure 7. Dwell time.

In the TTP Briefing, we exclude any MDR clients and measure dwell time from the initial date of the compromise until our IR team is engaged. This quarter, average dwell time continued to decrease, with 56% of incidents being resolved between 0-10 days. Shorter windows can mean faster detection, faster attacker execution, or both, and in Q3 we saw plenty of the latter.

What the shift says: Attackers are executing faster than we have ever seen. Some intrusions now play out in hours instead of days, with threat actors using AI tools to move through networks. Detection is improving, but so is attacker speed.

Review the full findings:

If you would like more information about this report, our team is available 24/7 at response@levelblue.com

Decrypting Full Disk Encryption with Dissect

Author: Guus Beckers

Back in 2022 Fox-IT decided to open source its proprietary incident response tooling known as Dissect. Since then it has been adopted by many different companies in their regular workflow. For those of you who are not yet familiar with Dissect, it is an incident response framework built with incident response engagements of any scale in mind. It allows you to extract artifacts from a variety of data formats and export them to a format of your choosing. Ever since Dissect has been open sourced a large number of individuals and institutions have contributed to the Dissect framework, culminating in the first Dissect partner day earlier in 2024.  

One of the most popular requests has been the capability to use Dissect in combination with common disk encryption methods like Microsoft’s BitLocker or its Linux equivalent LUKS. Internally at Fox-IT we were able to already use these capabilities. With the release of Dissect version 3.17 these capabilities are now also available to the community at large.  

Of course, a blog post is not complete without a demo. In this scenario a data acquisition has been performed against a disk protected with BitLocker. We are interested in a specific file located on the user’s desktop. During this scenario, a virtual machine was created with VMware Fusion which uses the .vmwarevm file format. Dissect can parse this format thanks to its associated loader.

First, we use Dissect to examine the disk properties:  

$ target-info "Windows 11 x64.vmwarevm" -v                                                                                                                                               
2024-11-27T11:57:18.474060Z [error    ] Failed to open an encrypted volume <Volume name='Basic data partition' size=67921509888 fs=None> with volume manager bitlocker: Failed to unlock BDE volume [dissect.target.volume] 
2024-11-27T11:57:18.634092Z [warning  ] <Target Windows 11 x64.vmwarevm>: Can't identify filesystem: <Volume name='Microsoft reserved partition' size=16776704 fs=None> [dissect.target.target] 
2024-11-27T11:57:19.416120Z [warning  ] <Target Windows 11 x64.vmwarevm>: Failed to find OS plugin, falling back to default [dissect.target.target] 
<Target Windows 11 x64.vmwarevm> 
 
 
Disks 
- <Disk type="VmdkContainer" size="68719476736"> 
 
 
Volumes 
- <Volume name="Basic data partition" size="104857088" fs="FatFilesystem"> 
- <Volume name="Microsoft reserved partition" size="16776704" fs="NoneType"> 
- <Volume name="Basic data partition" size="67921509888" fs="NoneType"> 
- <Volume name="part_fd7c00000" size="673185280" fs="NtfsFilesystem"> 
 
 
Hostname       : None 
Domain         : None 
Ips            : 
Os family      : default 
Os version     : None 
Architecture   : None 
Language       : 
Timezone       : None 
Install date   : 1970-01-01T00:00:00.000000+00:00 
Last activity  : None 

It seems the disk is encrypted, now we can use the latest version of BitLocker to decrypt the information.  Dissect supports three different types of decryption capabilities. An analyst can either use the user’s passphrase, the recovery key or can use a BitLocker file. Please check the updated documentation on the Dissect Docs page for more information.  For now we have created a keychain CSV file with the following information:  

$ cat keychain.csv 
bitlocker,recovery_key,,395791-328042-677721-279895-554466-214599-232023-709148 

We can use Dissect’s commands like target-info to check if the keychain works: 

$ target-info "Windows 11 x64.vmwarevm" -K keychain.csv                                                                                                                                     
2024-11-27T10:18:01.698079Z [warning  ] <Target Windows 11 x64.vmwarevm>: Can't identify filesystem: <Volume name='Microsoft reserved partition' size=16776704 fs=None> [dissect.target.target] 
2024-11-27T10:18:02.731474Z [warning  ] <Target Windows 11 x64.vmwarevm>: Empty hive: sysvol/windows/SECURITY [dissect.target.target] 
2024-11-27T10:18:02.737980Z [warning  ] <Target Windows 11 x64.vmwarevm>: Empty hive: sysvol/windows/SYSTEM [dissect.target.target] 
<Target Windows 11 x64.vmwarevm> 
 
 
Disks 
- <Disk type="VmdkContainer" size="68719476736"> 
 
 
Volumes 
- <Volume name="Basic data partition" size="104857088" fs="FatFilesystem"> 
- <Volume name="Microsoft reserved partition" size="16776704" fs="NoneType"> 
- <Volume name="Basic data partition" size="67921509888" fs="NoneType"> 
- <Volume name="part_fd7c00000" size="673185280" fs="NtfsFilesystem"> 
- <Volume name="Basic data partition" size="67921509888" fs="NtfsFilesystem"> 
 
 
Hostname       : SECRETDATAVM 
Domain         : None 
Ips            : 192.168.212.129 
Os family      : windows 
Os version     : Windows 11 Pro (NT 10.0) 26100.2314 
Architecture   : amd64-win64 
Language       : en_GB, en_NL, en_US 
Timezone       : Europe/Berlin 
Install date   : 2024-11-27T17:34:07.000000+00:00 
Last activity  : 2024-11-27T17:33:31.670376+00:00 

Alternatively, we can pass the recovery key value directly like this: 

$ target-info "Windows 11 x64.vmwarevm" -Kv 395791-328042-677721-279895-554466-214599-232023-709148 -v

Now we can browse through the decrypted filesystem and view the file on the user’s desktop: 

$ target-shell "Windows 11 x64.vmwarevm" -Kv 395791-328042-677721-279895-554466-214599-232023-709148 -q
                                                                                       
SECRETDATAVM:/$ cat c:/Users/Staff/Desktop/SuperSecretFile.txt 
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

As you can imagine this also works with Linux in the exact same manner.  This time we use a LUKS passphrase in conjunction with Dissect:

$ target-info "Ubuntu 64-bit 24.04.1.vmwarevm" -Kv glad-design-paper-airplane                                                                                                                          
2024-11-27T11:48:07.224355Z [warning  ] Failed to decode raw key as hex, ignoring: glad-design-paper-airplane [dissect.target.helpers.keychain] 
2024-11-27T11:48:08.910029Z [warning  ] <Target Ubuntu 64-bit 24.04.1.vmwarevm>: Can't identify filesystem: <Volume name='part_00100000' size=1048064 fs=None> [dissect.target.target] 
2024-11-27T11:48:09.826056Z [warning  ] <Target Ubuntu 64-bit 24.04.1.vmwarevm>: Unsupported mount device: /dev/disk/by-id/dm-uuid-LVM-YZiSLhoYFljS62k2vIjl3IcTwSkd0QguADKOf0a8t9am1jNdm9J1zerrDU7SWWFd / [dissect.target.target] 
<Target Ubuntu 64-bit 24.04.1.vmwarevm> 
2024-11-27T11:48:13.916382Z [warning  ] No timestamp found in one of the lines in /var/log/syslog! [dissect.target.helpers.utils] 
2024-11-27T11:48:13.925913Z [warning  ] Timestamp '27 2024 12:40:57' does not match format '%b %d %H:%M:%S', skipping line. [dissect.target.helpers.utils] 
2024-11-27T11:48:13.936096Z [warning  ] Timestamp 'Nov 2024 11:40:35' does not match format '%b %d %H:%M:%S', skipping line. [dissect.target.helpers.utils] 
2024-11-27T11:48:13.936416Z [warning  ] Timestamp 'Nov 2024 11:40:35' does not match format '%b %d %H:%M:%S', skipping line. [dissect.target.helpers.utils] 
2024-11-27T11:48:13.944841Z [warning  ] Timestamp 'Nov 2024 11:40:15' does not match format '%b %d %H:%M:%S', skipping line. [dissect.target.helpers.utils] 
2024-11-27T11:48:13.950083Z [warning  ] Timestamp 'Nov 2024 11:40:11' does not match format '%b %d %H:%M:%S', skipping line. [dissect.target.helpers.utils] 
2024-11-27T11:48:13.985809Z [warning  ] Timestamp 'Nov 2024 11:40:04' does not match format '%b %d %H:%M:%S', skipping line. [dissect.target.helpers.utils] 
2024-11-27T11:48:14.037897Z [warning  ] <Target Ubuntu 64-bit 24.04.1.vmwarevm>: Could not match cloud-init log line in file: /var/log/cloud-init.log [dissect.target.target] 
2024-11-27T11:48:14.037992Z [warning  ] <Target Ubuntu 64-bit 24.04.1.vmwarevm>: Could not match cloud-init log line in file: /var/log/cloud-init.log [dissect.target.target] 
2024-11-27T11:48:14.038056Z [warning  ] <Target Ubuntu 64-bit 24.04.1.vmwarevm>: Could not match cloud-init log line in file: /var/log/cloud-init.log [dissect.target.target] 
 
Disks 
- <Disk type="VmdkContainer" size="21474836480"> 
 
Volumes 
- <Volume name="part_00100000" size="1048064" fs="NoneType"> 
- <Volume name="part_00200000" size="1902116352" fs="ExtFilesystem"> 
- <Volume name="part_71800000" size="19569573376" fs="NoneType"> 
- <Volume name="part_71800000" size="19552796160" fs="NoneType"> 
- <Volume name="ubuntu--vg-ubuntu--lv" size="19549650944" fs="ExtFilesystem">
 
Hostname       : personnel-VMware-Virtual-Platform 
Domain         : None 
Ips            : 
Os family      : linux 
Os version     : Ubuntu 24.04.1 LTS (Noble Numbat) 
Architecture   : x86_64-linux 
Language       : en_US, en_US 
Timezone       : Europe/Amsterdam 
Install date   : 2024-11-27T11:33:29.665213+00:00 
Last activity  : 2024-11-27T11:45:34.821181+00:00 

We can use the same technique to extract another file from the Ubuntu desktop: 

$ target-shell "Ubuntu 64-bit 24.04.1.vmwarevm" -K keychain.csv -v                                                                                                                           
2024-11-27T11:59:52.227142Z [info     ] Registered key Key(key_type=<KeyType.PASSPHRASE: 'passphrase'>, value='glad-design-paper-airplane', provider='luks', identifier=None, is_wildcard=False) [dissect.target.helpers.keychain] 
2024-11-27T11:59:52.227562Z [info     ] Registered key Key(key_type=<KeyType.RECOVERY_KEY: 'recovery_key'>, value='395791-328042-677721-279895-554466-214599-232023-709148', provider='bitlocker', identifier=None, is_wildcard=False) [dissect.target.helpers.keychain] 
2024-11-27T11:59:53.719915Z [info     ] Volume <Volume name='part_71800000' size=19569573376 fs=None> unlocked with Key(key_type=<KeyType.PASSPHRASE: 'passphrase'>, value='glad-design-paper-airplane', provider='luks', identifier=None, is_wildcard=False) (keyslot: 0) [dissect.target.volumes.luks] 
2024-11-27T11:59:53.922164Z [warning  ] <Target Ubuntu 64-bit 24.04.1.vmwarevm>: Can't identify filesystem: <Volume name='part_00100000' size=1048064 fs=None> [dissect.target.target] 
2024-11-27T11:59:54.733524Z [info     ] <Target Ubuntu 64-bit 24.04.1.vmwarevm>: Found compatible OS plugin: DebianPlugin [dissect.target.target] 
2024-11-27T11:59:54.770648Z [info     ] <Target Ubuntu 64-bit 24.04.1.vmwarevm>: Found compatible OS plugin: LinuxPlugin [dissect.target.target] 
2024-11-27T11:59:54.791479Z [info     ] <Target Ubuntu 64-bit 24.04.1.vmwarevm>: Found compatible OS plugin: UnixPlugin [dissect.target.target] 
2024-11-27T11:59:54.802888Z [warning  ] <Target Ubuntu 64-bit 24.04.1.vmwarevm>: Unsupported mount device: /dev/disk/by-id/dm-uuid-LVM-YZiSLhoYFljS62k2vIjl3IcTwSkd0QguADKOf0a8t9am1jNdm9J1zerrDU7SWWFd / [dissect.target.target] 

personnel-VMware-Virtual-Platform:/$ cat /home/personnel/Desktop/secretLinuxfile 
"Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum."

Last but not least, Dissect also contains the fve-dd utility.  fve-dd can be used to decrypt an entire disk which allows a wider range of external tools to be used. fve-dd works on any supported Dissect containers. The individual VMDK files can be extracted from the .vmwarevm container:

$ ls                                                                                                                                                                                           
Virtual Disk-s001.vmdk Virtual Disk-s002.vmdk Virtual Disk-s003.vmdk Virtual Disk-s004.vmdk Virtual Disk-s005.vmdk Virtual Disk-s006.vmdk Virtual Disk.vmdk

Now the disk can be decrypted using fve-dd. The decryption can take some time depending on the size of the disk:

$ fve-dd -p glad-design-paper-airplane -o decrypted.dd "Virtual Disk.vmdk" -v

Dissect and other tools can be used on the decrypted disk:

$ target-info decrypted.dd                                                                                                                                                                     
[…]

Disks
- <Disk type="RawContainer" size="21458059264">

Volumes
- <Volume name="part_00100000" size="1048064" fs="NoneType">
- <Volume name="part_00200000" size="1902116352" fs="ExtFilesystem">
- <Volume name="part_71800000" size="19569573376" fs="NoneType">
- <Volume name="ubuntu--vg-ubuntu--lv" size="19549650944" fs="ExtFilesystem">

Hostname       : personnel-VMware-Virtual-Platform
Domain         : None
Ips            :
Os family      : linux
Os version     : Ubuntu 24.04.1 LTS (Noble Numbat)
Architecture   : x86_64-linux
Language       : en_US, en_US
Timezone       : Europe/Amsterdam
Install date   : 2024-11-27T11:33:29.665213+00:00
Last activity  : 2024-11-27T11:45:34.821181+00:00

Have fun with the latest version of Dissect!  

The Final Phase of the Incident Response Lifecycle: Lessons Learned

To close out this blog series on the six phases of incident response, we will discuss the final phase: Lessons Learned. This phase takes cybersecurity incidents and turns them into opportunities for growth and improvement, and emphasizes analyzing the response, identifying successes and shortcomings, and implementing enhancements to bolster future incident handling.

The Fourth Phase of the Incident Response Lifecycle: Eradication

After successfully containing a cybersecurity incident, the next crucial step is eradication, the fourth phase in the incident response lifecycle. Eradication involves completely removing malicious components from the organization's systems and addressing vulnerabilities that attackers exploited. Achieving thorough eradication ensures that threats do not linger or reoccur, allowing systems to be safely restored and future incidents prevented.

Understanding the Third Stage of the Incident Response Lifecycle: Containment

Containment is the third stage in the incident response lifecycle and it directly influences how quickly and effectively an organization can mitigate the impact of a cybersecurity incident. This phase aims to halt the spread of threats, minimize damage, and maintain operational continuity. Successful containment requires rapid decision-making, careful planning, and execution of immediate and long-term actions.

Incident Response: The Identification Phase

Timely identification of incidents is critical. The identification phase, the second stage in the six-phase incident response lifecycle, focuses on detecting, analyzing, and verifying security incidents as quickly and accurately as possible. Early and precise identification reduces potential damage, shortens recovery time, and significantly enhances overall cybersecurity posture.

Full-Disk Vulnerability Discovery: Uncovering Hidden Risks

Threat investigations rely on context to provide security teams with a clear picture of potential risks. This context comes from various sources, including telemetry, alert data, business impact, and risk assessments. One critical aspect of risk assessment is identifying open vulnerabilities on affected systems. This can help security teams determine whether known vulnerabilities are relevant to an active incident and how best to mitigate them.

Evolving Your Incident Response: Best Practices to Continuously Improve

As cloud environments grow more complex and attackers evolve their tactics, incident response strategies must continuously improve to remain effective. In a recent webinar, Cado experts Al Carchie and Shannon Lucas discussed key lessons from years of hands-on experience in incident response and shared best practices for organizations looking to strengthen their approach.

Top Free and Open-Source Forensics Tools

Digital forensics is a critical field dedicated to the identification, preservation, analysis, and presentation of digital evidence. As cyber threats evolve, so do the tools and techniques employed by forensic professionals. This blog looks into some of the top free and open-source digital forensics tools and the methodologies that are key to modern investigations.

Forensic Victory: Catching the Ransomware EDR Couldn't See

Endpoint Detection & Response (EDR) is frequently used by organizations as the first line of defense against cyber attacks. EDR platforms monitor organizations’ endpoints (servers, employee laptops, etc) and detect and contain malicious activity running where possible. In this blog, we will be exploring a ransomware attack in a lab environment, using payloads inspired from real attacks.

Cloud vs. On-Prem Forensics: The Differences You Need to Know

As organizations increasingly migrate workloads to the cloud, cybersecurity teams must adapt their digital forensics strategies. Investigating security incidents in a cloud environment presents challenges and opportunities distinct from traditional, on-premises forensics. The ability to efficiently collect, analyze, and respond to threats depends on understanding these key differences.

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