Insights from experts shaping secure development

An example scenario for a misconfiguration of Guice, which may lead to a NullPointerException being reported at runtime during testing.

我们预计，2021年是我们将一种全新类型的太空竞赛纳入主流的一年：保护我们的银河系免受网络欢迎。

该漏洞更像是人为问题或管理问题，它允许旧的 API 在本应被更新、更安全的版本所取代之后很长一段时间内仍然存在。

了解 Sensei 如何通过识别过时的模式并提示您提供后续使用的修复程序来帮助迁移。

渗透测试和静态分析扫描工具（俗称 SAST）只是降低安全风险的整个过程的一部分，它们的运行完全独立于我们的工作——当然，直到代码返回给我们进行修复！

Learn how Sensei can identify a coding pattern, and automatically generate a private constructor to make it impossible to instantiate the class.

无论不适感来自于未知的新工作方式、一点不信任，还是不相信远程办公，我都发现抵制远程办公的公司在吸引顶尖人才、保持全球影响力以及坦率地说，与时俱进方面往往会落后。

Learn how to use code reviews on pull requests to help enforce coding styles. And shorten the feedback cycle when pair programming with a more experienced programmer.

A quick example of creating a recipe to migrate from System.out.println to using a Java Logger.

日志和监控不足的漏洞主要是由于网络安全计划失败造成的，该计划涉及记录所有失败的身份验证尝试、拒绝访问和输入验证错误。

学习如何分享 Sensei 食谱并帮助团队中的每个人提高代码质量和生产力。

我们很高兴地宣布在 Secure Code Warrior 平台上发布全新功能：任务。这一全新的挑战类别是开发人员专属安全培训的下一阶段，它将用户从回忆安全知识转向将其应用于现实世界的仿真环境。

它在 API 中可能更为普遍，但攻击者通常会尝试在网络中的任何地方发现未修补的漏洞和未受保护的文件或目录。遇到一个启用了调试或禁用了安全功能的 API 只会让他们的恶意工作变得容易一些。

Learn how Sensei can help onboard developers and adopt new libraries.

Learn all about the latest updates to Sensei.

通过注解匹配示例，学习如何使用 Sensei 来匹配有问题的代码模式，然后将其修改为商定的实现。

大规格模分配漏洞的产出是由于许多现代架构的鼓鼓鼓鼓的开发人员使用自动将来自客户端的输入绑定到代码变量和内部对象的函数。

从澳大利亚政府认真对待网络安全的努力中可以明显看出，网络安全已被确定为国家层面的关键风险领域，但是他们的战略是否足够深远？

The Sensei plugin provides an easy way to find specific code patterns in your source code, and then apply rewrite rules to amend the matching code. All within the Intellij IDE, and in real-time.

Secure Code Warrior 开发了一个 GitHub Action，为GitHub代码扫描带来了情境学习。这意味着开发人员可以使用像 Snyk 容器操作这样的第三方操作来发现漏洞，然后通过 CWE 专用、高度相关的学习来增强输出。

缺少的功能级别访问控制漏洞允许用户执行应受限制的功能，或者允许他们访问应受保护的资源。

每个组织都可以利用网络安全宣传月来刷新他们的安全意识，今年，我们还为编程社区推出了一款新的免费应用程序！

当同时传入的请求过多，且 API 没有足够的计算资源来处理这些请求时，就会出现此漏洞。然后，该 API 可能变得不可用或无法响应新请求。

将安全补丁转移回开发流程并不容易，但在当今世界中，即使是像演示工具这样看似简单的设备也非常复杂，而且还能与其他所有设备联网，这是必要的。

该漏洞背后的实际机制与其他漏洞相似，但在这种情况下，过度数据泄露被定义为涉及受法律保护或高度敏感的数据。

身份验证通常既是应用程序的网关，也可能是通往网络其他部分的网关，因此它们是攻击者的诱人目标。如果身份验证过程中断或存在漏洞，攻击者很可能会发现该漏洞并加以利用。

我们想把焦点聚焦在我们的专家之一奥斯卡·昆塔斯身上。他是我们产品内容团队的一员，担任高级安全研究员。他还是我们在基础设施即代码 (IaC) 方面的常驻巫师。

通常，对于使用用户输入访问数据源的每个函数，都应包括对象级授权检查，不这样做会带来很大的风险。

网络攻击越来越频繁，影响基于Linux的基础设施的威胁也变得越来越普遍，最终目标是有机会破解存储在云中的敏感数据的战利品箱。

考虑到您的组织，请在您的角色背景下考虑这些问题。接受 DevSec 测试时表现如何？

精心策划的课程包含开发人员需要表现出熟练程度所需的确切模块，这将产生强大的影响，并使他们在日常工作中掌握安全最佳实践时能够从头开始。

我们已经知道工作日里有太多事情要做，那么开发人员需要什么动机去教室，或者切换情境，完成五个步骤才能获得基于静态理论的培训呢？

接触者追踪应用程序背后的想法是合理的。这项技术如果运行良好，将确保迅速发现热点并进行全面测试，这两者都是对抗传染性病毒传播的重要组成部分。

我们开始考虑我们可以做些什么来减少在你需要时接受培训的障碍，以及如何以更无缝的方式将微学习应用到你的工作流程中。

6月23日是极客日历中的一个特别条目，旨在纪念国际工程界女性日。这是我们阐明女性对软件开发的贡献的机会。

当程序员无法正确实现业务逻辑规则时，就会出现此漏洞，如果恶意用户选择利用这些规则，这可能会使他们的应用程序容易受到不同类型的攻击。

Rust 融合了常用语言中的已知和功能元素，采用了一种不同的理念，既考虑了复杂性，又引入了性能和安全性。

我们将在此重点讨论的诱发漏洞的行为是使用来自不可信来源的代码，这种看似良性的做法会造成重大问题。

医疗保健可能是下一个 “伟大” 的网络安全战场，犯罪分子攻击的正是诊断医疗问题、提供治疗和维持生命的机器。

安全配置错误，尤其是权限不当的配置错误，通常发生在开发人员完成任务并创建新用户或本应用程序权限时。

有时，应用程序还会与其他程序共享数据，这是总体工作负载的一部分。除非传输层受到保护，否则它很容易受到外部监听和未经授权的内部查看。

如今，对诸如密码、个人信息和财务记录之类的关键数据进行哈希处理是任何网络安全防御的基石。

传统的 COBOL 虽然是一种较旧的计算机语言，但至今仍然有效。从 Secure Code Warrior 了解有关 COBOL 安全应用程序开发的更多信息。

如今，大多数计算机安全的关键都涉及密码。即使采用其他安全方法，例如双因素身份验证或生物识别，大多数组织仍将基于密码的安全性作为其保护要素之一。

我们必须进入这样一个阶段，即安全被视为整个组织乃至整个 SDLC 的共同责任。当你承诺使用一个成熟的、高度支持的 DevSecOps 环境时，这肯定是可能的。

如果基础设施级别的访问控制不完善，它就会向攻击者开放整个企业，攻击者可以利用该漏洞作为未经授权的窥探或全面攻击的门户。

攻击者总是会首先尝试找到易于利用的漏洞，甚至可能使用脚本来修复常见的漏洞。这与小偷检查街上的所有汽车以查看是否有门被解锁没什么不同，这比砸窗户容易得多。

这是关于组织内PCI-DSS合规性的迷你系列的第二部分。在最后一章中，我们将详细介绍首席技术官和首席信息安全官如何从高层领导降低网络风险，使流程顺畅、成功... 也许还能为开发人员带来一点乐趣。

这是关于组织内部成功合规 PCI-DSS 的系列文章的第 1 部分，共分为两部分。在本章中，我们将详细介绍 AppSec 专家如何与开发经理密切合作，以增强开发人员的能力，加强 SSDLC 并从一般立法中获得具体成果。

在我们的行业中，许多安全专家已经开始预测今年的热点问题，但是由于2019年有超过50亿条敏感数据记录被盗，我们认为预测在可预见的将来网络安全不会发生的事情会更加准确。

围绕 “向左移动” 的许多举措，即在开发过程的早期引入安全性，根本无法起到足够的作用。

随着GDPR的出台，以及在多阶段攻击暴露了许多公众人物以及德国联邦政府服务器的敏感数据之后的战略的修订，很明显，网络安全意识和行动是DACH地区领导人的头等大事。

世界开始走过瀑布、敏捷和现在的 DevOps，那么下一个解决方案是什么？作为一名开发人员，你在跟上这些方法变化方面扮演什么角色？

去年年底，MITRE的精彩社区发布了2019年CWE影响全球的25大最危险软件错误清单。而且大部分都不足为奇。

我本可以从所有事实和数据开始写这篇文章，说明一家蓬勃发展、高速增长的初创公司；不可否认，它们给人留下了深刻的印象，而且我们持续的公司发展轨迹也很强劲。但是，对我来说，这些数字并不能反映我在2019年最引以为豪的事情。

很少有公司能真正成功实施 DevOps。但是，在整个企业中提供正确的支持、培育和理解可以改变您的流程。

美国国家标准与技术研究所（NIST）发布了更新的白皮书，详细介绍了减少软件漏洞和网络风险的几项行动计划。

这些开发以人为中心的活动是日历上我最喜欢的活动之一；它们是 “卑斯地提醒” 社区不是 “地下人” 和 “增强” 软件工程师和专家的能力，使他们能够在工作中保持安全。

尽管监管举措无疑将随着时间的推移而得到改善和发展，但如果各组织现在已经按下了紧急按钮并开始接受培训，他们可能会发现自己没有为未来做好准备。

有来自各行各业的各种类型的开发人员，而且我们所做的每件事都具有社区意识。

尽管安全编码需要成为高等教育阶段软件工程的必备组成部分，但一些大学从一开始就在提供一流培训和优先考虑安全性方面处于领先地位。p

我们的客户成功副总裁Fatemah Beydoun最近向非常乐于接受的听众发表了她的演讲，“指导未来：我们如何在培养女性网络安全人才方面做得更好”。她一直是推动网络安全行业积极变革不可或缺的一部分。

每当应用程序将反序列化的数据视为可信数据时，就会发生不安全的反序列化。如果用户能够修改新重建的数据，他们就可以执行各种恶意活动，例如代码注入、拒绝服务攻击或提升权限。

令人难以置信的是，许多地方仍然依赖教室、枯燥的教科书和乏味的视频培训来让自己的最佳和最聪明的人参与新举措，尤其是在有一种更好、更具吸引力、更有价值的学习方式：情境式培训时。

软件安全行业并不完全以其温暖而模糊的感受、异想天开的观察和生活评论而闻名，但是，也许随着年龄的增长，我发现自己正在反思我们所有人可能对世界产生的影响。

每当仅供授权查看的信息在未加密、未保护或保护薄弱的状态下暴露给未经授权的人时，就会发生敏感数据泄露。

青少年安全研究员比尔·德米尔卡皮揭露了学校使用的软件中的主要漏洞，这无疑让人回想起。我记得我还是个好奇的孩子，打开了软件的盖子，偷看下面，看看它是如何运作的... 以及我能否破解它。

尽管对于普通消费者来说，VxWorks 并不是家喻户晓的名字，但这款软件产品每天都会使许多人受益，就像你我一样。现在，我们面临着数亿台基于VxWorks的设备遭到入侵的可能性。

XML 外部实体注入攻击（有时简称为 XXE 注入）相对较新，但它目前在黑客社区中非常受欢迎，而且随着成功的积累，这种攻击甚至会越来越多。

如果攻击者可以在现实的应用程序中插入 CR 或 LF 代码，他们有时间可以对其行为进行改进。与大多数人攻击相比，其影响不太大，但对目标进行组织化的危险也同样严重。

富有创造力、鼓舞人心的首席信息安全官员和首席信息官员能量创新，塑造我们的数字世界，但他们也可以改变变量组织的安全文明方面发作重要作用。

在许多方面，远程文件包含漏洞比其本地文件漏洞危险得多，也更容易被利用。因此，应尽快找到并予以补救。

今年，PCI安全标准委员会发布了一套全新的软件安全指南，作为其PCI软件安全框架的一部分。此更新旨在使软件安全最佳实践与现代软件开发保持一致。

与许多漏洞不同，利用本地文件包含和路径遍历过程实现恶意目的需要足够熟练的攻击者、相当长的时间，可能还需要一点运气。

即使您已经完全保护了应用程序服务器及其使用的后端系统，但如果传输层保护不足，通信仍可能容易受到窥探。

XML 注入攻击是黑客发明的令人讨厌的小漏洞，目的是帮助他们破坏托管 XML 数据库的系统。这包括人们在考虑传统数据库时想到的各种东西，即从药物到电影等任何事物的详细信息存储。

英国华为网络安全评估中心最近的一份报告确定了华为软件工程流程中的主要安全问题。但这是一个可以解决的问题。

针对诸如如何充分利用组织的 AppSec 预算等热点问题，以及听众提出的几个棘手问题，AppSec小组提供了一些真正的早间魔法，将帮助安全专家在其组织内制定可行的计划。

记录和监控不足是应用程序防御结构中可能存在的最危险的情况之一。如果存在此漏洞或情况，那么几乎所有针对它的高级攻击最终都会成功。

对能够处理未经验证的重定向和转发的网站或应用程序进行编码对您的用户和组织来说都极其危险。

这是官方消息：我们正在与Bugcrowd联手对开发人员进行安全编码方面的教育、赋权和启发。

代码注入攻击是许多网站和应用程序将遇到的最常见，也是最危险的攻击之一。它们在复杂性和构成的危险方面无所不包，但是几乎所有接受用户输入的网站或应用程序都可能存在漏洞。

最近对GitHub存储库的攻击凸显了安全行业中一个众所周知的问题：大多数开发人员根本不够安全意识，宝贵的数据随时可能面临风险。

在构建业务应用程序时，无论是供客户内部使用还是外部使用，都可能不会让每个用户执行每一项功能。如果这样做，则可能容易受到访问控制中断的影响。

随着网络攻击的增加——影响各个垂直领域的各类组织——代价高昂、令人尴尬和影响利润的数据泄露的威胁是真实存在的。问题不是变小，而是像肿瘤一样生长。

当你的网络应用程序泄露了很多信息时，它会使攻击者更容易进入这些信息。在这篇文章中，我们将介绍什么是信息泄露、它为何危险，以及如何防止。

由于所有应用程序都使用组件，其中大部分是您尚未编写的，因此您使用的组件中的漏洞可能会成为负担。让我们讨论使用具有已知漏洞的组件意味着什么，它有多危险，以及如何解决这个问题。

我一直站在两边，我非常清楚开发团队和AppSec专家之间在维护安全最佳实践方面可能出现的紧张关系。但是，有更好的方法。

我们将介绍运营网站或允许员工远程访问计算机资源的组织（几乎是所有人）面临的最常见问题之一。是的，你可能猜到我们将要谈论身份验证。

如果应用程序没有足够的反自动化检查，攻击者只需猜测密码直到找到匹配的密码即可。以下是阻止他们的方法。

尽管编码问题可能是问题的一部分，但业务逻辑错误通常是由首次创建应用程序时的设计缺陷或错误的逻辑假设造成的。

在网络安全领域，我们通常就像猎人一样。我们的眼睛紧紧地注视着地平线，正在寻找下一个突破漏洞。但是，这种前瞻性的关注可能会产生令人惊讶的效果，削弱我们的整体安全意识。

网站和应用程序通常允许用户使用电子邮件通过应用程序发送反馈和其他各种信息。而且大多数人甚至没有从潜在的安全风险的角度来考虑这个问题。

直接对象引用是指在应用程序中引用特定记录（“对象”）。它通常采用唯一标识符的形式，可能出现在 URL 中。

软件安全一直是我的头等大事，我们日益数字化的个人信息共享生活方式所构成的真正危险也是如此。毕竟，我们处在一个基本上不受监管、无人监督、被忽视的领域。我们在狂野的西部。

在这个数字社会中，开发人员有责任保护信息和企业免受不安全的加密存储的影响。向安全代码勇士学习。

绝大多数网站使用XML数据库来执行关键功能，例如保存用户登录凭证、客户信息、个人身份信息以及机密或敏感数据，这使得XQuery攻击的攻击足迹相当大。

什么是安全配置错误？找出最常见的安全配置错误以及如何防止漏洞。向安全代码勇士学习。

我女儿和公司年纪越大，我就越意识到创业之旅和 “初次做母亲” 的旅程之间有很多相似之处。我现在都已经是第四年了。pi

现在让我们来看看点击劫持是如何工作的，为什么它很危险，以及像你这样的开发者可以做些什么来防止这种情况。

Kamer van Koophandel shares how it embedded secure coding into everyday development through role-based certifications, Trust Score benchmarking, and a culture of shared security ownership.

See how Paysafe's partnership with Secure Code Warrior led to a 45% boost in developer productivity and a major reduction in code vulnerabilities.

DigitalOcean's use of Secure Code Warrior training has significantly reduced security debt, allowing teams to focus more on innovation and productivity. The improved security has strengthened their product quality and competitive edge. Looking ahead, the SCW Trust Score will help them further enhance security practices and continue driving innovation.

Explore the Devlympics 2023 results in this report. Dive into developer engagement, tech stack and languages trends in each industry that participated, and key vulnerabilities and CWEs covered in the annual global event hosted by Secure Code Warrior.

Discover how Sage enhanced security with a flexible, relationship-focused approach, creating 200+ security champions and achieving measurable risk reduction.

Discover how Workday transformed developer training with agile learning through Secure Code Warrior. By empowering developer with hands-on, language-specific education, Workday reduced vulnerabilities early in the SDLC. See their impressive results and key takeaways to build a secure code culture.

In this case study, learn how Thales has developed people, process, and technology approaches for an agile secure code learning program in order to engage developers to become active security champions.

Discover how retail giant Colgate-Palmolive reshaped its application security during its digital transformation journey. Facing challenges in secure coding, they innovated their approach by integrating bite-sized, in-context learning into the developer workflow.

Learn how Blue Prism, the global leader in intelligent automation for the enterprise, used Secure Code Warrior's agile learning platform to create a security-first culture with their developers, achieve their business goals, and ship secure code at speed

IAG Group is the name behind many of the leading insurancecompanies in the Asia-Pacific region, underwriting policies formillions of customers to the tune of approximately AUD $11.4 Billionin premiums per annum.

Learn how they created an in-house technology education initiative, aimed at supporting thousands of employees to learn practical, cutting-edge skills in a number of disciplines, including machine learning and cybersecurity.

Explore this comprehensive case study to learn more about how they utilized Secure Code Warrior's tournaments to engage developers, increase awareness of key vulnerabilities affecting automotive software, and gain metrics across multiple languages and frameworks.

​The cybersecurity industry, which has been advocating for “security by design” principles for more than a decade, stands in wide-eyed amazement at the risks posed by artificial intelligence (AI). As organizations rush to embrace AI enablement, a CISO’s most pressing priority is to avoid becoming a roadblock. However, without effective AI usage and governance, observability and traceability, organizations may be blindsided by their AI risk.​

Secure Code Warrior has introduced the SCW AI Adoption Model, a framework designed to help organisations govern AI use in software development as the industry shifts from the traditional software development lifecycle (SDLC) toward what the company calls the Agentic Development Lifecycle (ADLC).

With many software engineering teams moving from AI coding assistants into full agentic AI code generation and increasing the amount of code they produce exponentially, ensuring the security of that code must be a top priority. The study produces practical guidance for organizations that are getting on board the AI-assisted or agentic code development train.

Token use can create unexpected, sizeable costs for organizations.

AI enables faster development cycles and allows developers to focus on higher-value work. For many businesses, these efficiencies are becoming essential to remaining competitive. The challenge, therefore, is not whether to adopt AI, but how to do so responsibly. Businesses that invest in developer education, governance frameworks, AI observability and robust security controls will be better positioned to capture the benefits while limiting the associated risks.

The issue is no longer simply about protecting AI models themselves. Increasingly, attackers are focusing on the software ecosystem surrounding those models, including the development tools, middleware, open-source libraries, and automated deployment pipelines that organisations rely upon every day.

As we will unpack together, there is a lot of movement around the world, with some collaboration between nations, but the path forward is far from uniform or clear, particularly in business environments where AI adoption is often mandated before holistic safeguarding measures are in place.  

According to one expert, AI guardrails are not designed as “security boundaries” but rather to influence behaviour – but what if that behaviour is hacking one of your industry partners?

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Cyber security experts have warned that the breach of Hugging Face infrastructure during an OpenAI security evaluation marks a turning point in the risks posed by autonomous AI agents. In the incident, AI models moved beyond a controlled test and carried out a live, multi-stage intrusion against the AI platform.

AI-generated code introduces an average of 15 confirmed vulnerabilities per codebase, research published by Secure Code Warrior indicates.

Frontier AI is facing a PR crisis. After Hugging Face released a blog post on July 16 claiming an autonomous agent had breached its internal environment, OpenAI posted on July 21 that the incident occurred when GPT 5.6 Sol and a “pre-release model” escaped a controlled testing environment.

Secure Code Warrior research reveals AI-generated code introduces an average of 15 vulnerabilities per codebase.

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Secure Code Warrior introduced the SCW AI Trust Index, a living benchmark for AI coding security that grows with every new model, helping organizations understand and govern the security risks introduced by AI-generated code. Built on a methodology created with RMIT University, Australia, then extended by Secure Code Warrior, the research presents comprehensive benchmarks on how often leading LLMs produce insecure code, with material implications for every enterprise scaling AI-assisted development.

AI-generated code introduces 15 vulnerabilities on average per codebase, but the actual risk depends on framework pairing more than the model used.

New SCW AI Trust Index shows AI-generated coding risk is not random, it's predictable by model and framework, giving security leaders the data to safely scale AI-assisted development.

The challenges with AI implementation, constant updates, and the race for industry dominance are coming thick and fast, and security professionals are among the most affected by its vast risk profile.

The Australian government has said AI is very much in the country’s future national interest – but where does it stand today? Here’s what the industry’s best and brightest have to say about artificial intelligence and its role in the modern enterprise.

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The emergence of agentic AI marks a structural shift in software development, introducing systems that not only accelerate production cycles but also perform autonomous reasoning and action beyond direct human control.

As AI-generated code becomes commonplace, CISOs need new audit strategies to measure developer practices, govern AI tool usage, and identify software risks before they reach production.

This category has taken on new urgency in 2026 for a reason that’s specific to this moment: AI coding tools and agents are dramatically increasing how much code gets written and how often it needs to be deployed, tested, and provisioned for. Platform engineering is the layer that determines whether that increased velocity translates into shipped value or into chaos.

According to a recent report from Gartner, the rampant use of shadow AI and rogue automation is further fueling the proliferation of AI vulnerabilities. Gartner notes that 32% of IT workers using generative AI tools at work say they keep them hidden from cybersecurity teams. Combined with low-code/no-code platforms and vibe coding practices, the AI copilots are greatly expanding the enterprise attack surface.

For this article, we asked a central question for security and risk leaders: "What differentiates a policy that genuinely mitigates enterprise risk from one that exists primarily to demonstrate that the organization has acknowledged AI risk?"

Secure Code Warrior's Pieter Danhieux on Managing AI-Driven Development Risks

As generative AI cements its place in enterprise software development, a familiar discipline is taking on new urgency: risk management.

Secure Code Warrior have today announced SCW Trust Agent: AI, the industry’s first governance solution designed to make Artificial Intelligence (AI) influence in software development visible, attributable, and enforceable at the point of commit — enabling enterprises to scale AI coding tools with measurable control over software risk.

Even as we restructure the SDLC around the most impactful elements of the Agile methodology with careful, DevSecOps-centric security considerations, is this the end of the road for AppSec as we know it?

Global InfoSec Awards 2026 Secure Code Warrior Wins Outstanding Achievement in Cybersecurity Risk Management and Compliance Excellence

New AI Software Governance solution makes AI-generated code visible at commit, enforces policy before production, and connects real development behavior to measurable risk reduction.

Secure Code Warrior (SCW) this week added an artificial intelligence (AI) agent that both identifies code generated by an AI coding tool and automatically applies the appropriate governance policies.

Secure Code Warrior has launched SCW Trust Agent: AI, a software governance product that tracks the use of AI coding tools in development and links that usage to software risk when developers commit code.

2026 Globee® Awards for Cybersecurity: Secure Code Warrior Wins Gold Globee for Software Development Cybersecurity Solutions (Best Of)

Secure Code Warrior announced SCW Trust Agent: AI, a governance solution designed to make AI influence in software development visible, attributable, and enforceable at the point of commit — enabling enterprises to scale AI coding tools with measurable control over software risk.

Secure Code Warrior today announced SCW Trust Agent: AI, the industry’s first governance solution designed to make AI influence in software development visible, attributable, and enforceable at the point of commit — enabling enterprises to scale AI coding tools with measurable control over software risk. For the first time, organizations can trace which AI models influenced specific commits, correlate that influence to vulnerability exposure, and take corrective action before insecure code reaches production.

Secure Code Warrior has announced SCW Trust Agent: AI, a governance solution designed to make AI influence in software development visible, attributable, and enforceable at the point of commit, enabling enterprises to scale AI coding tools with measurable control over software risk. Organizations can trace which AI models influenced specific commits, correlate that influence with vulnerability exposure, and take corrective action before insecure code reaches production.

New AI Software Governance solution makes AI-generated code visible at commit, enforces policy before production, and connects real development behavior to measurable risk reduction.

Developers have long struggled to truly claim a seat at the table in traditional threat modeling programs, but with the right skills, they have the opportunity to wield AI responsibly to seriously cut risk and rework in their codebase.

AI-generated code may be “made by machine”, but taking a cookie-cutter approach to securing that code would fall well short of mitigating the vulnerabilities LLMs can introduce. Organizations need to establish precise security reviews, with human developers anchoring the process to implement effective security controls while also managing the specific coding temperament of each LLM used. AI-generated code must undergo the same personalized risk assessments as code written by human developers.

s artificial intelligence (AI) tools become more widely used in the software development process, their impact on security is becoming clearer. According to recent research, nearly 70% of organisations have discovered vulnerabilities caused by AI tools while one in five have experienced a serious incident as a result of those vulnerabilities.

According to research company Forrester[1], the tech debt for 75% of organisations will increase to a moderate or high level during this year, due to the rapid expansion of AI usage across a range of areas including software development.

While it’s early into 2026, we’re seeing new research that reveals the extent of cyber risks caused by artificial intelligence (AI)-assisted software development: Nearly 7 in 10 organizations have discovered vulnerabilities introduced by AI-generated code, and 1 in 5 have suffered a serious incident tied directly to the vulnerabilities.

Artificial intelligence (AI) has rapidly become indispensable to modern software development. From large language models that generate code on demand to agentic systems that automate entire workflows, AI tools promise dramatic gains in productivity and efficiency.

Developers must view AI as a collaborator to be closely monitored, rather than an autonomous entity to be unleashed. Without such a mindset, crippling tech debt is inevitable.

From technical compromise to AI-driven attacks, cyber criminals increasingly see software developers as prime targets, creating systemic risks CISOs must address.

It’s Online Privacy Week, a time of year where individuals and organisations are all reminded to check their digital footprint(s). Some might say that’s a futile gesture at a time where major social media and marketing players know absolutely everything about you and are cheerfully selling all that data to anyone who’ll buy it; when Microsoft is performing every trick in the book to get Windows users to put all their data in the cloud where it’s available for government agencies to snoop upon without letting you know; when a personal computer crisis means many people will be moved on to dumb-client computing landscape where everything from data storage to major processing tasks will be taking place in the cloud; and when people think that clicking ‘Accept’ on website pop-ups does something that meaningfully protects them. But, what do the experts say?

Technology and data specialists have warned that artificial intelligence and weak data governance are sharpening privacy risks for organisations, as businesses mark World Data Privacy Day.

“Data Privacy Week" presents a great reminder for organisations to reassess their customer privacy policies and prioritise transparent data collection in their marketing strategies.

Five leading cybersecurity experts warn AI is being integrated faster than security policies can manage the risk, creating urgent privacy gaps for SMEs ahead of Data Protection Day on 28 January.

The OWASP Foundation has been a guiding light for security professionals and enthusiasts alike, providing critical, practical advice on the most insidious software vulnerabilities across a plethora of categories and platforms. It has been the first major update since 2021 to the flagship OWASP Top 10 Web Vulnerabilities, and in that time, the industry has been rocked by a stampede of AI technology, tools, and code, each creating a dichotomy of security efficiency and risk for both cybersecurity and software engineering professionals.