Blog

Thought Leadership

Generative AI: How Darktrace AI protects 8,400 customers from security and privacy risks

Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
12
2023年6月
12
2023年6月
本ブログでは、Darktrace DETECTおよびRESPOND が、生成AIに関連するプライバシーおよびセキュリティのリスクを低減するために組織を支援する方法を説明します。

生成AIや大規模言語モデル(LLM)は今年、一般の人々の意識の主流になりました。OpenAIのChatGPTやGoogle Bardを、ウェブ検索の支援から職場の効率化を促進するためのAI機能に至るまで、あらゆることに利用しています。

Darktrace では、AI が現代において最も変革的な技術的機会のひとつとなる可能性を、長い間理解してきました。ケンブリッジにある当社のサイバーAIリサーチセンターは、10年以上にわたってAIツールの研究開発を行ってきました。Darktrace DETECTやRESPONDのようなツールは、さまざまなAI技術を駆使して、世界中の8,400社の顧客をサイバー破壊から保護しています。 

AIのパイオニアとして、また世界を変える可能性を理解する者として、私たちは2023年、ついにAIの魔神が瓶から出てしまったと認識しています。AIツールは急速に私たちの日常生活の一部となりつつあるのです。 

アクティブな顧客の74%において、従業員が職場で生成AIツールを使用している [1]

生成AIツールは生産性を向上させ、人間の創造性を補強する力を持つ一方で、企業はイノベーションのペースに遅れないように迅速に対応する必要があります。これらのツールは、使い方を誤ったり、ビジネス特有のニーズに合った適切なポリシーが適用されなかったりすると、潜在的なプライバシーリスクやセキュリティリスクを誘発し、CISOにとっての悩みの種となります。

生成AIによるプライバシーとセキュリティのリスク 

英国の国家サイバーセキュリティセンター(NCSC)のような政府機関はすでに、生成AIツールやその他のLLMを職場で使用する際のリスク管理の必要性に関するガイダンスを発表しています。米国では、サイバーセキュリティインフラストラクチャー庁(CISA)も、生成AIのセキュリティへの影響について懸念を表明しています。

その理由のひとつは、LLMがプロンプトから学習し、入力された情報を保存してデータセットの訓練に使用できるからです。そのデータがシステムにあれば、誰かが正しいプロンプトを入力すれば、LLMはその問い合わせに対して貴社のデータを利用できる可能性があるのです。

また、入力した情報に知的財産やノウハウ、財務報告書、社内の機密文書、販売数などの機密ファイルやデータが含まれている場合、適切なガードレールが設置されていなければ、第三者のAIモデルの一部となって他者が利用できる可能性があり、プライバシー、知的財産、セキュリティ上のリスクが発生します。 

Darktrace が生成AIの利用を管理するのに役立つ方法 

生成AIツールの利用が拡大していることを受け、Darktrace のお客様が知的財産の損失やデータ漏えいのリスクに関する懸念に対応するための新しいリスクおよびコンプライアンスモデルを発表しました。

私たちは、これらの生成AIツールが、人々や企業の効率的な作業を支援する機能を備えた非常に強力なものであることに興奮していますが、他のテクノロジーと同様に、正しく管理または監視されない場合、不注意に悪用される可能性があるというリスクも理解しています。そのため、Darktrace DETECTとRESPONDの新しいリスクとコンプライアンスモデルは、AutoGPT、ChatGPT、Stable Diffusion、Claudeなどの生成AIとLLMツールのアクティビティと接続を監視し、必要に応じて対応するためのガードレールを設置することを容易にします。 

生成AIツールに関連する独自の明確なポリシーとニーズは各々の企業が擁しており、我々もまた、お客様が監視するツールのリストを独自に追加することが容易になりました。 

Darktraceの自己学習型AIは、会社のポリシーやベストプラクティスから逸脱する可能性のある生成AIの活動を検知することができます。当社は、お客様のデータにAIを導入し、すべてのユーザー、資産、およびデバイスの日々の動作を学習し、お客様のビジネス固有の「生活パターン」の理解を構築します。 そのため、ビジネスへの脅威を示すわずかな異常もリアルタイムに検知し、自律的に対応することができ、数秒で脅威を封じ込めることができるのです。  

2023年5月、Darktrace の自己学習型AIが、ある顧客の生成AIツールに対する1GBを超えるデータのアップロードを検知し、阻止しました。 [2]

これらのガードレールがあることで、Darktrace のお客様は、潜在的なセキュリティ、IP、およびプライバシーのリスクから保護されたまま、生成AIとLLMを使用する機会をフル活用することができます。

安全で責任あるAIの活用

Darktraceでは、最近の生成AI と LLM の進歩は、サイバーセキュリティを変革する AI 技術の武器になる重要な追加要素だと考えています。LLMや生成AIを含むAI技術は、長年にわたり当社の全製品で活用されており、インシデントのリアルタイム分析を行うCyber AI Analystを含め、Darktrace のお客様がAIの力を駆使してサイバー脅威から保護され続けることを支援しています。

しかし、当社はまた、様々なAI技術の責任ある開発と展開を信じています。だからこそ当社はお客様が安全かつ責任を持ってAIを使用するために必要なツールを提供しています。 

Darktraceの自己学習型AIは、過去10年間にわたり、すでに8,400社以上の企業がサイバー脅威や混乱に対処し、自らを保護するのに役立っています。これらの新しいツールを使用することで、CISOは潜在的なセキュリティリスクを心配することなく、生成AIによって生産性を確実に向上させることができます。当社のAIは、リアルタイムかつ常時ビジネスを学習しており、セキュリティの成果向上へのインパクトは非常に大きいものです。

自己学習型AIは、DarktraceのサイバーAIループ(サイバー攻撃を予防、検知、遮断、修復するための継続的なフィードバックループを作成するために自律的に連携して動作する、動的に関連する機能の相互接続された包括的なセット)に反映されます。データ、人、企業がサイバー脅威から完全自律的に確実に保護されるようにする当社のミッションです。

図1:Darktrace サイバーAIループ

参考文献

2023年6月2日に取得した、Call Homeを有効にしたアクティブなお客様の環境から、Darktrace がある時点で生成AIの活動を検知したデータに基づきます。

2023年6月2日に取得した、Call Homeを有効にしたアクティブなお客様の自社環境から、Darktrace がある時点で生成AIの活動を検知したデータに基づきます。

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.
AUTHOR
ABOUT ThE AUTHOR
Jack Stockdale OBE
Chief Technology Officer

Jack Stockdale is the founding CTO at Darktrace. With over 20 years’ experience of software engineering, Jack is responsible for overseeing the development of Bayesian mathematical models and artificial intelligence algorithms that underpin Darktrace’s award-winning technology. Jack and his development team in Cambridge were recognized for their outstanding contribution to engineering by the Royal Academy of Engineering MacRobert Innovation Award Committee in 2017 and again in 2019. Jack has a degree in Computer Science from Lancaster University.

Book a 1-1 meeting with one of our experts
この記事を共有
USE CASES
該当する項目はありません。
COre coverage
該当する項目はありません。

More in this series

該当する項目はありません。

Blog

Inside the SOC

A Thorn in Attackers’ Sides: How Darktrace Uncovered a CACTUS Ransomware Infection

Default blog imageDefault blog image
24
Apr 2024

What is CACTUS Ransomware?

In May 2023, Kroll Cyber Threat Intelligence Analysts identified CACTUS as a new ransomware strain that had been actively targeting large commercial organizations since March 2023 [1]. CACTUS ransomware gets its name from the filename of the ransom note, “cAcTuS.readme.txt”. Encrypted files are appended with the extension “.cts”, followed by a number which varies between attacks, e.g. “.cts1” and “.cts2”.

As the cyber threat landscape adapts to ever-present fast-paced technological change, ransomware affiliates are employing progressively sophisticated techniques to enter networks, evade detection and achieve their nefarious goals.

How does CACTUS Ransomware work?

In the case of CACTUS, threat actors have been seen gaining initial network access by exploiting Virtual Private Network (VPN) services. Once inside the network, they may conduct internal scanning using tools like SoftPerfect Network Scanner, and PowerShell commands to enumerate endpoints, identify user accounts, and ping remote endpoints. Persistence is maintained by the deployment of various remote access methods, including legitimate remote access tools like Splashtop, AnyDesk, and SuperOps RMM in order to evade detection, along with malicious tools like Cobalt Strike and Chisel. Such tools, as well as custom scripts like TotalExec, have been used to disable security software to distribute the ransomware binary. CACTUS ransomware is unique in that it adopts a double-extortion tactic, stealing data from target networks and then encrypting it on compromised systems [2].

At the end of November 2023, cybersecurity firm Arctic Wolf reported instances of CACTUS attacks exploiting vulnerabilities on the Windows version of the business analytics platform Qlik, specifically CVE-2023-41266, CVE-2023-41265, and CVE-2023-48365, to gain initial access to target networks [3]. The vulnerability tracked as CVE-2023-41266 can be exploited to generate anonymous sessions and perform HTTP requests to unauthorized endpoints, whilst CVE-2023-41265 does not require authentication and can be leveraged to elevate privileges and execute HTTP requests on the backend server that hosts the application [2].

Darktrace’s Coverage of CACTUS Ransomware

In November 2023, Darktrace observed malicious actors leveraging the aforementioned method of exploiting Qlik to gain access to the network of a customer in the US, more than a week before the vulnerability was reported by external researchers.

Here, Qlik vulnerabilities were successfully exploited, and a malicious executable (.exe) was detonated on the network, which was followed by network scanning and failed Kerberos login attempts. The attack culminated in the encryption of numerous files with extensions such as “.cts1”, and SMB writes of the ransom note “cAcTuS.readme.txt” to multiple internal devices, all of which was promptly identified by Darktrace DETECT™.

While traditional rules and signature-based detection tools may struggle to identify the malicious use of a legitimate business platform like Qlik, Darktrace’s Self-Learning AI was able to confidently identify anomalous use of the tool in a CACTUS ransomware attack by examining the rarity of the offending device’s surrounding activity and comparing it to the learned behavior of the device and its peers.

Unfortunately for the customer in this case, Darktrace RESPOND™ was not enabled in autonomous response mode during their encounter with CACTUS ransomware meaning that attackers were able to successfully escalate their attack to the point of ransomware detonation and file encryption. Had RESPOND been configured to autonomously act on any unusual activity, Darktrace could have prevented the attack from progressing, stopping the download of any harmful files, or the encryption of legitimate ones.

Cactus Ransomware Attack Overview

Holiday periods have increasingly become one of the favoured times for malicious actors to launch their attacks, as they can take advantage of the festive downtime of organizations and their security teams, and the typically more relaxed mindset of employees during this period [4].

Following this trend, in late November 2023, Darktrace began detecting anomalous connections on the network of a customer in the US, which presented multiple indicators of compromise (IoCs) and tactics, techniques and procedures (TTPs) associated with CACTUS ransomware. The threat actors in this case set their attack in motion by exploiting the Qlik vulnerabilities on one of the customer’s critical servers.

Darktrace observed the server device making beaconing connections to the endpoint “zohoservice[.]net” (IP address: 45.61.147.176) over the course of three days. This endpoint is known to host a malicious payload, namely a .zip file containing the command line connection tool PuttyLink [5].

Darktrace’s Cyber AI Analyst was able to autonomously identify over 1,000 beaconing connections taking place on the customer’s network and group them together, in this case joining the dots in an ongoing ransomware attack. AI Analyst recognized that these repeated connections to highly suspicious locations were indicative of malicious command-and-control (C2) activity.

Cyber AI Analyst Incident Log showing the offending device making over 1,000 connections to the suspicious hostname “zohoservice[.]net” over port 8383, within a specific period.
Figure 1: Cyber AI Analyst Incident Log showing the offending device making over 1,000 connections to the suspicious hostname “zohoservice[.]net” over port 8383, within a specific period.

The infected device was then observed downloading the file “putty.zip” over a HTTP connection using a PowerShell user agent. Despite being labelled as a .zip file, Darktrace’s detection capabilities were able to identify this as a masqueraded PuttyLink executable file. This activity resulted in multiple Darktrace DETECT models being triggered. These models are designed to look for suspicious file downloads from endpoints not usually visited by devices on the network, and files whose types are masqueraded, as well as the anomalous use of PowerShell. This behavior resembled previously observed activity with regards to the exploitation of Qlik Sense as an intrusion technique prior to the deployment of CACTUS ransomware [5].

The downloaded file’s URI highlighting that the file type (.exe) does not match the file's extension (.zip). Information about the observed PowerShell user agent is also featured.
Figure 2: The downloaded file’s URI highlighting that the file type (.exe) does not match the file's extension (.zip). Information about the observed PowerShell user agent is also featured.

Following the download of the masqueraded file, Darktrace observed the initial infected device engaging in unusual network scanning activity over the SMB, RDP and LDAP protocols. During this activity, the credential, “service_qlik” was observed, further indicating that Qlik was exploited by threat actors attempting to evade detection. Connections to other internal devices were made as part of this scanning activity as the attackers attempted to move laterally across the network.

Numerous failed connections from the affected server to multiple other internal devices over port 445, indicating SMB scanning activity.
Figure 3: Numerous failed connections from the affected server to multiple other internal devices over port 445, indicating SMB scanning activity.

The compromised server was then seen initiating multiple sessions over the RDP protocol to another device on the customer’s network, namely an internal DNS server. External researchers had previously observed this technique in CACTUS ransomware attacks where an RDP tunnel was established via Plink [5].

A few days later, on November 24, Darktrace identified over 20,000 failed Kerberos authentication attempts for the username “service_qlik” being made to the internal DNS server, clearly representing a brute-force login attack. There is currently a lack of open-source intelligence (OSINT) material definitively listing Kerberos login failures as part of a CACTUS ransomware attack that exploits the Qlik vulnerabilities. This highlights Darktrace’s ability to identify ongoing threats amongst unusual network activity without relying on existing threat intelligence, emphasizing its advantage over traditional security detection tools.

Kerberos login failures being carried out by the initial infected device. The destination device detected was an internal DNS server.
Figure 4: Kerberos login failures being carried out by the initial infected device. The destination device detected was an internal DNS server.

In the month following these failed Kerberos login attempts, between November 26 and December 22, Darktrace observed multiple internal devices encrypting files within the customer’s environment with the extensions “.cts1” and “.cts7”. Devices were also seen writing ransom notes with the file name “cAcTuS.readme.txt” to two additional internal devices, as well as files likely associated with Qlik, such as “QlikSense.pdf”. This activity detected by Darktrace confirmed the presence of a CACTUS ransomware infection that was spreading across the customer’s network.

The model, 'Ransom or Offensive Words Written to SMB', triggered in response to SMB file writes of the ransom note, ‘cAcTuS.readme.txt’, that was observed on the customer’s network.
Figure 5: The model, 'Ransom or Offensive Words Written to SMB', triggered in response to SMB file writes of the ransom note, ‘cAcTuS.readme.txt’, that was observed on the customer’s network.
CACTUS ransomware extensions, “.cts1” and “.cts7”, being appended to files on the customer’s network.
Figure 6: CACTUS ransomware extensions, “.cts1” and “.cts7”, being appended to files on the customer’s network.

Following this initial encryption activity, two affected devices were observed attempting to remove evidence of this activity by deleting the encrypted files.

Attackers attempting to remove evidence of their activity by deleting files with appendage “.cts1”.
Figure 7: Attackers attempting to remove evidence of their activity by deleting files with appendage “.cts1”.

結論

In the face of this CACTUS ransomware attack, Darktrace’s anomaly-based approach to threat detection enabled it to quickly identify multiple stages of the cyber kill chain occurring in the customer’s environment. These stages ranged from ‘initial access’ by exploiting Qlik vulnerabilities, which Darktrace was able to detect before the method had been reported by external researchers, to ‘actions on objectives’ by encrypting files. Darktrace’s Self-Learning AI was also able to detect a previously unreported stage of the attack: multiple Kerberos brute force login attempts.

If Darktrace’s autonomous response capability, RESPOND, had been active and enabled in autonomous response mode at the time of this attack, it would have been able to take swift mitigative action to shut down such suspicious activity as soon as it was identified by DETECT, effectively containing the ransomware attack at the earliest possible stage.

Learning a network’s ‘normal’ to identify deviations from established patterns of behaviour enables Darktrace’s identify a potential compromise, even one that uses common and often legitimately used administrative tools. This allows Darktrace to stay one step ahead of the increasingly sophisticated TTPs used by ransomware actors.

Credit to Tiana Kelly, Cyber Analyst & Analyst Team Lead, Anna Gilbertson, Cyber Analyst

付録

参考文献

[1] https://www.kroll.com/en/insights/publications/cyber/cactus-ransomware-prickly-new-variant-evades-detection

[2] https://www.bleepingcomputer.com/news/security/cactus-ransomware-exploiting-qlik-sense-flaws-to-breach-networks/

[3] https://explore.avertium.com/resource/new-ransomware-strains-cactus-and-3am

[4] https://www.soitron.com/cyber-attackers-abuse-holidays/

[5] https://arcticwolf.com/resources/blog/qlik-sense-exploited-in-cactus-ransomware-campaign/

Darktrace DETECT Models

Compromise / Agent Beacon (Long Period)

Anomalous Connection / PowerShell to Rare External

Device / New PowerShell User Agent

Device / Suspicious SMB Scanning Activity

Anomalous File / EXE from Rare External Location

Anomalous Connection / Unusual Internal Remote Desktop

User / Kerberos Password Brute Force

Compromise / Ransomware / Ransom or Offensive Words Written to SMB

Unusual Activity / Anomalous SMB Delete Volume

Anomalous Connection / Multiple Connections to New External TCP Port

Compromise / Slow Beaconing Activity To External Rare  

Compromise / SSL Beaconing to Rare Destination  

Anomalous Server Activity / Rare External from Server  

Compliance / Remote Management Tool On Server

Compromise / Agent Beacon (Long Period)  

Compromise / Suspicious File and C2  

Device / Internet Facing Device with High Priority Alert  

Device / Large Number of Model Breaches  

Anomalous File / Masqueraded File Transfer

Anomalous File / Internet facing System File Download  

Anomalous Server Activity / Outgoing from Server

Device / Initial Breach Chain Compromise  

Compromise / Agent Beacon (Medium Period)  

Compromise / Agent Beacon (Long Period)  

IoC一覧

IoC - Type - Description

zohoservice[.]net: 45.61.147[.]176 - Domain name: IP Address - Hosting payload over HTTP

Mozilla/5.0 (Windows NT; Windows NT 10.0; en-US) WindowsPowerShell/5.1.17763.2183 - User agent -PowerShell user agent

.cts1 - File extension - Malicious appendage

.cts7- File extension - Malicious appendage

cAcTuS.readme.txt - Filename -Ransom note

putty.zip – Filename - Initial payload: ZIP containing PuTTY Link

MITRE ATT&CK マッピング

Tactic - Technique  - SubTechnique

Web Protocols: COMMAND AND CONTROL - T1071 -T1071.001

Powershell: EXECUTION - T1059 - T1059.001

Exploitation of Remote Services: LATERAL MOVEMENT - T1210 – N/A

Vulnerability Scanning: RECONAISSANCE     - T1595 - T1595.002

Network Service Scanning: DISCOVERY - T1046 - N/A

Malware: RESOURCE DEVELOPMENT - T1588 - T1588.001

Drive-by Compromise: INITIAL ACCESS - T1189 - N/A

Remote Desktop Protocol: LATERAL MOVEMENT – 1021 -T1021.001

Brute Force: CREDENTIAL ACCESS        T – 1110 - N/A

Data Encrypted for Impact: IMPACT - T1486 - N/A

Data Destruction: IMPACT - T1485 - N/A

File Deletion: DEFENSE EVASION - T1070 - T1070.004

続きを読む
著者について
Tiana Kelly
Deputy Team Lead, London & Cyber Analyst

Blog

該当する項目はありません。

The State of AI in Cybersecurity: How AI will impact the cyber threat landscape in 2024

Default blog imageDefault blog image
22
Apr 2024

About the AI Cybersecurity Report

We surveyed 1,800 CISOs, security leaders, administrators, and practitioners from industries around the globe. Our research was conducted to understand how the adoption of new AI-powered offensive and defensive cybersecurity technologies are being managed by organizations.

This blog is continuing the conversation from our last blog post “The State of AI in Cybersecurity: Unveiling Global Insights from 1,800 Security Practitioners” which was an overview of the entire report. This blog will focus on one aspect of the overarching report, the impact of AI on the cyber threat landscape.

To access the full report click here.

Are organizations feeling the impact of AI-powered cyber threats?

Nearly three-quarters (74%) state AI-powered threats are now a significant issue. Almost nine in ten (89%) agree that AI-powered threats will remain a major challenge into the foreseeable future, not just for the next one to two years.

However, only a slight majority (56%) thought AI-powered threats were a separate issue from traditional/non AI-powered threats. This could be the case because there are few, if any, reliable methods to determine whether an attack is AI-powered.

Identifying exactly when and where AI is being applied may not ever be possible. However, it is possible for AI to affect every stage of the attack lifecycle. As such, defenders will likely need to focus on preparing for a world where threats are unique and are coming faster than ever before.

a hypothetical cyber attack augmented by AI at every stage

Are security stakeholders concerned about AI’s impact on cyber threats and risks?

The results from our survey showed that security practitioners are concerned that AI will impact organizations in a variety of ways. There was equal concern associated across the board – from volume and sophistication of malware to internal risks like leakage of proprietary information from employees using generative AI tools.

What this tells us is that defenders need to prepare for a greater volume of sophisticated attacks and balance this with a focus on cyber hygiene to manage internal risks.

One example of a growing internal risks is shadow AI. It takes little effort for employees to adopt publicly-available text-based generative AI systems to increase their productivity. This opens the door to “shadow AI”, which is the use of popular AI tools without organizational approval or oversight. Resulting security risks such as inadvertent exposure of sensitive information or intellectual property are an ever-growing concern.

Are organizations taking strides to reduce risks associated with adoption of AI in their application and computing environment?

71.2% of survey participants say their organization has taken steps specifically to reduce the risk of using AI within its application and computing environment.

16.3% of survey participants claim their organization has not taken these steps.

These findings are good news. Even as enterprises compete to get as much value from AI as they can, as quickly as possible, they’re tempering their eager embrace of new tools with sensible caution.

Still, responses varied across roles. Security analysts, operators, administrators, and incident responders are less likely to have said their organizations had taken AI risk mitigation steps than respondents in other roles. In fact, 79% of executives said steps had been taken, and only 54% of respondents in hands-on roles agreed. It seems that leaders believe their organizations are taking the needed steps, but practitioners are seeing a gap.

Do security professionals feel confident in their preparedness for the next generation of threats?

A majority of respondents (six out of every ten) believe their organizations are inadequately prepared to face the next generation of AI-powered threats.

The survey findings reveal contrasting perceptions of organizational preparedness for cybersecurity threats across different regions and job roles. Security administrators, due to their hands-on experience, express the highest level of skepticism, with 72% feeling their organizations are inadequately prepared. Notably, respondents in mid-sized organizations feel the least prepared, while those in the largest companies feel the most prepared.

Regionally, participants in Asia-Pacific are most likely to believe their organizations are unprepared, while those in Latin America feel the most prepared. This aligns with the observation that Asia-Pacific has been the most impacted region by cybersecurity threats in recent years, according to the IBM X-Force Threat Intelligence Index.

The optimism among Latin American respondents could be attributed to lower threat volumes experienced in the region, but it's cautioned that this could change suddenly (1).

What are biggest barriers to defending against AI-powered threats?

The top-ranked inhibitors center on knowledge and personnel. However, issues are alluded to almost equally across the board including concerns around budget, tool integration, lack of attention to AI-powered threats, and poor cyber hygiene.

The cybersecurity industry is facing a significant shortage of skilled professionals, with a global deficit of approximately 4 million experts (2). As organizations struggle to manage their security tools and alerts, the challenge intensifies with the increasing adoption of AI by attackers. This shift has altered the demands on security teams, requiring practitioners to possess broad and deep knowledge across rapidly evolving solution stacks.

Educating end users about AI-driven defenses becomes paramount as organizations grapple with the shortage of professionals proficient in managing AI-powered security tools. Operationalizing machine learning models for effectiveness and accuracy emerges as a crucial skill set in high demand. However, our survey highlights a concerning lack of understanding among cybersecurity professionals regarding AI-driven threats and the use of AI-driven countermeasures indicating a gap in keeping pace with evolving attacker tactics.

The integration of security solutions remains a notable problem, hindering effective defense strategies. While budget constraints are not a primary inhibitor, organizations must prioritize addressing these challenges to bolster their cybersecurity posture. It's imperative for stakeholders to recognize the importance of investing in skilled professionals and integrated security solutions to mitigate emerging threats effectively.

To access the full report click here.

参考文献

1. IBM, X-Force Threat Intelligence Index 2024, Available at: https://www.ibm.com/downloads/cas/L0GKXDWJ

2. ISC2, Cybersecurity Workforce Study 2023, Available at: https://media.isc2.org/-/media/Project/ISC2/Main/Media/ documents/research/ISC2_Cybersecurity_Workforce_Study_2023.pdf?rev=28b46de71ce24e6ab7705f6e3da8637e

続きを読む
著者について
Our ai. Your data.

Elevate your cyber defenses with Darktrace AI

無償トライアルを開始
Darktrace AI protecting a business from cyber threats.