Insights from experts shaping secure development

安全编码项目若想取得成功，仅有优质内容是不够的。赋能要素 8 将展示如何通过品牌塑造，将参与过程转化为一种令人向往且具有身份象征的体验。

企业技术格局正以一种鲜有人预料到的速度发生剧变。我们已正式跨越了从人工编写代码和基础辅助编程，迈向“智能体开发生命周期”（ADLC）的时代。虽然自主 AI 智能体在多项职能中展现出前所未有的效率，但也带来了全新的安全与合规风险。

认可激发参与。赋能要素 7 旨在通过奖励和专属礼品大张旗鼓地庆祝开发者的成就，以此彰显真正且来之不易的安全编码成果。

Secure Code Warrior 入选 2026 年 Gartner® 应用安全技术成熟度曲线（Hype Cycle™），涵盖“代理式编码安全”与“安全编码培训”类别。原因如下。

在全面采用某款 AI 模型之前，请先查阅我们专有的 LLM 基准测试数据——SCW AI 信任指数。

高管支持并非一劳永逸。第 6 项赋能要素将展示如何通过定期汇报，让领导层持续关注、了解并投入到项目的成功中。

了解 Secure Code Warrior 为何转型为渠道优先型公司，以及值得信赖的合作伙伴如何帮助企业安全、大规模地采用 AI 软件治理。

Secure Code Warrior 专为非开发人员打造的 AI 素养计划。

Secure Code Warrior 今日发布了一份全新的白皮书，其中涵盖了一种指导性的 AI 采用模型。安全领导者可以利用该模型识别自身所处的采用阶段，并切实有效地管控组织内部的 AI 安全风险。

告别“一劳永逸”的培训模式。Enabler 5 可构建多级认证计划，为开发人员提供明确的进阶路径并验证其专业技能。

NSA 发布了首份 MCP 安全指南。SCW 的课程体系已覆盖其中 23 个问题中的 18 个——以下是具体的映射情况。

Gartner 两度点名 SCW。随着 AI 智能体在开发工作中发挥越来越大的作用，SCW 为您提供安全采用 AI 驱动开发所需的各项能力与治理手段。

Adaptive Learning 将 SCW Trust Agent 与我们的整个学习平台无缝连接，确保培训内容与开发者的实时工作保持高度同步。

将安全编码培训与实际的 AI 开发活动相结合——无需人工干预，即可自动为使用 AI 工具的开发人员分配指导。将安全编码培训与实际的 AI 开发活动相结合——无需人工干预，即可自动为使用 AI 工具的开发人员分配指导。

自适应学习会自动为引入实际漏洞的开发人员分配针对性的安全编码培训，从源头上降低重复风险。Secure Code Warrior 博客横幅，背景为一名开发人员在多显示器工作台前编写代码，上方覆盖蓝色图层，标题为“针对开发人员代码中的实际风险进行培训”。

通过“赋能要素 4：低门槛用户访问”消除安全编码计划中的阻力。探索 SSO、预置式入职引导和中继状态策略，让开发人员只需点击一下即可开始培训。

我非常自豪地宣布，Secure Code Warrior 已与亚马逊云科技（AWS）签署了战略合作协议。鉴于威胁形势的迅速演变，对于安全领导者和着眼未来的开发者而言，此次战略合作正当其时，意义重大。

我非常高兴地宣布，Secure Code Warrior 与 KnowBe4 即将达成战略合作伙伴关系。KnowBe4 是全球领先的综合性人力与智能体 AI 风险管理专家，是协助我们将基础安全意识推广至全球各地的理想合作伙伴。

后量子密码学（PQC）对于保护数据免受量子计算威胁至关重要。了解“先截获，后解密”策略如何带来风险，以及开发人员应如何为量子安全做好准备。

利用强有力的沟通计划，让开发者持续参与您的安全编码项目。学习如何突出项目优势、把握沟通基调并庆祝取得的成果。

Anthropic 的 Claude Mythos 标志着每位安全领导者在规划安全项目时必须进行根本性的永久转变，尤其是在处理遗留系统的补丁管理方面。

Explore Enabler 2: Senior Leadership Sponsorship. Learn why active buy-in from the CIO, CTO, and CISO is vital to drive developer adoption and program credibility.

While development teams look to make the most of GenAI’s undeniable benefits, we’d like to propose a four-point foundational framework that will allow security leaders to deploy AI coding tools and agents with a higher, more relevant standard of security best practices. It details exactly what enterprises can do to ensure safe, secure code development right now, and as agentic AI becomes an even bigger factor in the future.

Cybermon 2025 打败老板现已在 SCW 中全年开幕。部落高级 AI/LLM 安全战，大规格模加强安全 AI 开发。

Anthropic’s launch of Claude Code Security marks a defining collision point between AI-assisted software development, and the rapid augmentation of how we approach modern cybersecurity.

了解《欧盟网络弹性法案》(CRA) 的要求、适用于谁以及工程团队如何通过设计实践、漏洞预防和开发人员能力建设做好准备。

Enabler 1 是我们由 10 部分组成的成功推动者系列的序幕，它展示了如何将安全编码与业务成果（例如降低风险和提高长期计划成熟度的速度）联系起来。

2025 was a big year for AI, for cybersecurity, and for SCW. I’m approaching 2026 with quiet confidence, and the optimism that only hard work paying off can bring.

Secure Code Warrior’s 10 Enablers guide organizations in building lasting secure coding programs by focusing on people, process, and program maturity stages.

OWASP 2025 年前 10 名将软件供应链故障列为 #3。通过严格的 SBOM、依赖关系跟踪和 CI/CD 管道强化来缓解这种高影响风险。

OWASP Top 10 2025 adds Mishandling of Exceptional Conditions at #10. Mitigate risks via "fail closed" logic, global error handlers, and strict input validation.

了解 OWASP Top 10：2025 中发生了哪些变化，以及 Secure Code Warrior 如何通过更新的任务、课程和开发者见解轻松过渡。

Is the cybersecurity world moving too fast on agentic AI? The future of AI security is here, and it's time for experts to move from reflection to reality.

Trust Agent by Secure Code Warrior solves the secure coding crisis, validating dev proficiency on every commit. It discovers all contributors & automates governance in your dev workflow.

人工智能的争论不在于使用，而是应用。了解如何依靠深入了解其代码的开发人员，在提高 AI 生产力的需求与强大的安全性之间取得平衡。

In our latest whitepaper, our co-founders Pieter Danhieux and Dr. Matias Madou, Ph.D., explore the double-edged sword that is AI Coding Assistants and how they can be a welcome addition and a significant security liability at the same time.

借助这份可操作的指南，应对贵组织的网络安全风险，以进行有效的网络安全风险评估。

CISOs can’t rely on the same old awareness playbook. In the Age of AI, they must embrace modern approaches to safeguard code, teams, and organizations.

Learn how Trust Agent: AI provides deep visibility and governance over AI-generated code, empowering organizations to innovate faster and more securely.

人工智能辅助编码正在改变开发。试试我们全新的 Copilot 风格的人工智能挑战赛，在现实的工作流程中安全地审查、分析和修复代码。

介绍我们为期 12 周的免费 AI/LLM 安全视频系列！了解人工智能辅助编码的基本风险以及如何构建更安全的应用程序。

Your all-in-one guide to our 12-week AI/LLM security video series. Catch every episode, learn key AI security concepts, and follow along weekly.

了解安全编码的真正含义以及安全编码实践如何降低公司的漏洞和安全相关成本。

庆祝 10,000 多场安全代码学习活动，以及十年来帮助开发人员降低低风险风险、提高高代码质量并自信地处理 AI 辅助 AI 辅助助开开发。

人工智能辅助开发已不在眼前——它就在这里，它正在迅速重塑软件的编写方式。GitHub Copilot、Cline、Roo、Cursor、Aider和Windsurf等工具正在将开发人员转变为自己的副驾驶，从而加快迭代速度，加速从原型设计到重大重构项目的所有工作。

When reflecting on our own technology, SCW’s Developer Risk Management platform, I am buoyed by recent metrics from one of our core enterprise clients, and going down the proverbial rabbit hole into this data tells a tale of a high-adoption, potent Secure by Design initiative that has been proven to considerably reduce risk in their organization.

Secure Code Warrior很高兴地宣布我们与进攻性安全解决方案领导者HackerOne进行了新的整合。我们正在共同建立一个强大的综合生态系统。HackerOne 查明了现实环境中漏洞实际发生的位置，暴露了安全问题的 “内容” 和 “在哪里”。

在我们最新的白皮书中，我们的联合创始人彼得·丹希厄和马蒂亚斯·马杜博士与包括首席信息安全官、AppSec领导人和安全专业人员在内的二十多位企业安全领导者进行了座谈，找出了这个难题的关键部分，并揭示了安全由设计运动背后的现实。这是安全团队的共同抱负，但没有共同的策略。

Vibe 编程就像大学兄弟会派对，而人工智能是所有庆祝活动的核心，小桶。放松身心，发挥创造力，看看你的想象力可以带你走向何方，这很有趣，但是在喝了几个小桶之后，适量饮酒（或者使用人工智能）无疑是更安全的长期解决方案。

编码代理是如何被欺骗编写容易进行 SQL 注入的代码、安装外壳工具甚至跟踪其用户的

任务使开发者能够通过交互式学习、降低风险和优化开发来掌握安全编码

Secure Code Warrior 的创始团队一直团结在一起，在整整十年中指导飞船度过每一次教训、胜利和挫折。作为开发者风险管理领域的领导者，我们正在扩大规模，准备迎接我们的下一个篇章——SCW 2.0。

组织在使用人工智能来支持长期生产力、可持续性和安全投资回报率方面面临着艰难的决定。在过去的几年中，我们很清楚，人工智能永远不会完全取代开发者的角色。从 AI + 开发人员合作伙伴关系到围绕 Secure-by-Design 期望的日益增加的压力（和困惑），让我们仔细看看明年的预期。

利用最新的 OWASP 十大更新，在保护 LLM 应用程序方面保持领先地位。了解新增内容、变化以及 Secure Code Warrior 如何为您提供最新的学习资源，以降低生成式 AI 中的风险。

我们的研究表明，安全代码培训是有效的。Trust Score使用了一种算法，该算法利利用了来自600多个组织的25万多名学者从工作中获得的超额超过2000万个学习数据点，展示了其在低速降低漏洞的有效性以及如何使该计划更有效。

The idea of bringing preventive security to legacy code and systems at the same time as newer applications can seem daunting, but a Secure-by-Design approach, enforced by upskilling developers, can apply security best practices to those systems. It’s the best chance many organizations have of improving their security postures.

人们越来越关注安全代码和安全设计原则，这要求开发人员从SDLC一开始就接受网络安全培训，Secure Code Warrior的信任评分等工具可以帮助衡量和改善他们的进度。

我们最新的研究论文《基准安全技能：简化企业中的安全设计》是对企业层面真正的安全设计计划进行深入分析的结果，并根据数据驱动的发现得出最佳实践方法。

在我们探索通用 UNIX 打印系统 (CUPS) 中最近出现的高严重性漏洞时，了解 Linux 用户面临的最新安全挑战。了解这些问题如何可能导致潜在的远程代码执行 (RCE)，以及您可以采取哪些措施来保护系统。

跨站脚本 (XSS) 利用 BROWSER 的信使和用户的无知来取走数据、接管帐户和破坏者网站；这个漏洞很快，会变得非常快。让我们来看看 XSS 是如何工作的，可以造成什么伤害以及如何防止。

了解我们新的参与度洞察报告，该报告提供了深入的分析，可帮助您衡量安全代码学习成果。

Secure Code Warrior从一开始就帮助DigitalOcean构建和发布高质量的代码，与具有安全意识的开发人员一起推动数字创新和现代化。

Secure-by-Design is the latest initiative on everyone’s lips, and the Australian government, collaborating with CISA at the highest levels of global governance, is guiding a higher standard of software quality and security from vendors.

由 Secure Code Warrior 推出的 SCW Trust Agent 为安全领导者提供了在组织内扩展开发人员驱动的安全性所需的可见性和控制力。通过连接到代码存储库，它可以评估代码提交元数据，检查开发人员、使用的编程语言和交付时间戳，以确定开发人员的安全知识。

网络安全战略计划推出了大多数人组织网络安全方程式的重量大变化，开发人处的工作人员帮助实现了这些新目标的独家地位。

It's becoming apparent that while cybersecurity platforms and defenses are critical components in defense against modern attacks, what is truly needed is secure code that can be deployed free from vulnerabilities. And that requires security-aware developers with verified security skills.

全面了解我们的敏捷学习方法、Microsoft 团队集成以及我们的开发参与报告。

使用安全代码勇士为您的开发人员提供支持。我们的平台为开发人员提供按需学习内容并赋予其权力。

查看 SCW 信任分数，深入了解组织安全和开发人员能力。

管理金融服务行业的法规，例如PCI DSS，强调了安全代码的重要性以及对开发人员进行安全最佳实践培训的必要性。

在主要 Linux 发行版使用的 XZ Utils 数据压缩库中发现了一个名为 CVE-2024-3094 的严重漏洞，该漏洞是由威胁行为者通过后门程序引入的。这种高严重性问题允许潜在的远程代码执行，对软件构建过程构成重大风险。该漏洞影响了Fedora Rawhide中XZ Utils的早期版本（5.6.0和5.6.1），并紧急呼吁各组织实施补丁。该事件凸显了社区志愿者在维护开源软件方面的关键作用，并凸显了在软件开发生命周期内加强安全措施和访问控制的必要性。

生成式人工智能为金融服务公司提供了很多优势，但也带来了很多潜在风险。培训开发人员掌握安全最佳实践并将其与 AI 模型配对，有助于从一开始就创建安全代码。

Secure Code Warrior和Mend.io讨论了人工智能对安全性的影响、主动安全方法以及漏洞警报的有效管理。

了解 Secure Code Warrior 与 Apiiro 的最新集成。

了解 Secure Code Warrior 平台的最新改进以及即将推出的改进。

通过遵循安全编码惯例，开发人员可以帮助保护其应用程序免受攻击者利用的漏洞的侵害。正如精心建造的房屋不太可能倒塌一样，编码良好的应用程序也不太可能被黑客入侵。

敏捷学习通过持续学习加速问题解决并提高开发人员效率。

尽管LLM式的人工智能技术似乎不可避免地会改变我们处理许多方面的工作方式，而不仅仅是软件开发，但我们必须退后一步，考虑头条新闻之外的风险。作为编程伙伴，它的缺陷可能是它最为 “人性化” 的属性。

今天是我们的九岁生日，随着形势的持续快速变化，我对我们在网络安全领域取得的成就和持久的地位感到非常自豪和感激。

大量复杂的安全工具使网络安全对首席信息安全官来说更具挑战性。

安全代码勇士对2024年及以后网络安全行业的十大预测。

SCW 案例研究博客，重点介绍了 Netskope 部署的敏捷学习环境。

探索 AI 在软件开发中的安全风险，并学习如何使用 Secure Code Warrior 有效应对这些挑战。

为开发人员提供分层方法，以减少漏洞、增进关系并对反复出现的问题进行优先排序。

Explore Secure Code Warrior’s 2023 journey to empower developers, enhance productivity, and mitigate risk in cybersecurity with recent innovations to our agile learning platform.

由于持续的技能短缺与为满足世界软件需求而编写的大量代码背道而驰，许多企业的网络安全战略和现有基础设施都落在了后面。现在是我们诚实地审视我们的整体网络安全成熟度，并评估摆在我们面前的可行速赢的时候了。

安全领导者需要重新考虑开发人员从安全代码学习体验中获得的价值，以及如何使该计划更具吸引力，最重要的是，更具影响力。在本博客中，我们将探讨如何通过更多的实践学习和与工具的集成，让开发人员对安全代码教育感到兴奋，从而取得重大成果，并将引入的漏洞减少多达 53%。

通过 Secure Code Warrior 的动手敏捷安全培训，了解如何减少漏洞和安全漏洞。

受影响的 curl 库版本容易受到基于堆的缓冲区溢出漏洞的影响，该漏洞与 SOCKS5 代理协议的传统问题有关。学习如何通过可玩的任务来查找和修复这种漏洞类型。

首席信息安全官发现自己处于越来越紧张的境地：保护更多资产，发布更多代码，减少更大的攻击面，并利用迅速减少的财务资源来做到这一点。网络安全被视为成本中心是不可避免的事实，尽管组织的安全计划阻碍了威胁行为者成为明天的灾难性头条，但安全领导者必须采取更多措施，用对执行机构来说合理的语言进行推销和证明该部门的整体商业价值。

MoveIT场景与许多开发人员和AppSec专业人员以前可能经历的场景略有不同，你可以在这里的实时模拟中测试你的SQLI-slaying技能。

Secure Code Warrior 的新增功能：为多家公司设置锦标赛、新的编码指南、为用户提供 SCIM 资源等等！

可以肯定地说，过去几年对网络安全标准进行了变革，尽管这不是强制性的，但所有组织都应该是该死的，仔细审查供应商安全实例，就好像它是自己的部落安全计划的一部分一样。

荷兰商会（Kamer van Koophandel）分享了他们如何通过基于角色的认证、信任评分基准测试以及共享安全责任的文化，将安全编码融入日常开发工作。

了解 Paysafe 如何通过与 Secure Code Warrior 的合作，将开发人员生产力提升 45%，并大幅减少代码漏洞。

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.

请通过本报告探索 2023 年 Devlympics 的比赛结果。深入了解各参赛行业的开发者参与度、技术栈与编程语言趋势，以及本次由 Secure Code Warrior 主办的年度全球赛事中所涵盖的关键漏洞与 CWE。

了解 Sage 如何通过灵活且以关系为导向的方法增强安全性，成功培养了 200 多名安全倡导者，并实现了可衡量的风险降低。

了解 Workday 如何通过 Secure Code Warrior 的敏捷学习模式革新开发者培训。通过为开发者提供实操性的语言专属课程，Workday 在软件开发生命周期（SDLC）的早期阶段就有效降低了漏洞风险。查看他们的显著成果与核心经验，助力构建安全编码文化。

在本案例研究中，了解泰雷兹（Thales）如何通过人员、流程和技术方法构建敏捷的安全代码学习计划，从而激励开发人员成为积极的安全倡导者。

了解零售巨头高露洁棕榄（Colgate-Palmolive）如何在数字化转型过程中重塑其应用安全。面对安全编码方面的挑战，他们通过将碎片化、情境化的学习融入开发人员的工作流程，实现了创新。

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 集团是亚太地区多家领先保险公司的幕后推手，每年为数百万客户承保的保费总额约达 114 亿澳元。

了解他们如何创建了一项内部技术教育计划，旨在支持数千名员工学习包括机器学习和网络安全在内的多个学科中实用且前沿的技能。

请阅读这份详尽的案例研究，了解他们如何利用 Secure Code Warrior 的竞赛功能来提升开发人员的参与度，增强对汽车软件关键漏洞的认知，并获取跨多种语言和框架的衡量指标。

Secure Code Warrior has launched Citizen AI, an AI literacy training programme for non-developer employees intended to support responsible AI adoption across business functions.

New AI literacy program equips non-developer employees with the judgment, risk awareness and responsible-use habits needed to safely adopt AI-powered workflows.

Secure Code Warrior announced Citizen AI by Secure Code Warrior, a new AI literacy program designed specifically for non-developer employees to help organizations build a workforce ready for responsible AI adoption. Citizen AI helps organizationsreduce AI-related human risk, support broader enterprise AI governance initiatives, increase employee confidence when using AI and accelerate the safe adoption of AI-powered workflows.

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Secure Code Warrior, a leader in AI software governance and developer security upskilling, today announced Citizen AI by Secure Code Warrior, a new AI literacy program designed specifically for non-developer employees to help organizations build a workforce ready for responsible AI adoption.

全新的 AI 素养计划旨在为非开发人员提供必要的判断力、风险意识和负责任的使用习惯，助力企业安全采用 AI 驱动的工作流程。

Organizations are missing a big target when developing governance and developer training programs for AI-assisted software development.

AI software development continues to evolve at a rapid pace for developers and their teams. , CEO & Co-Founder at Secure Code Warrior, posits that as the norm shifts from human-written code to AI-assisted coding and agentic workflows, many security teams now face a critical challenge: managing the new risks that autonomous systems introduce.

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The question facing software development shops isn’t whether Generative AI should be used to create software code, or whether the percentage of code generated by GenAI will increase in the near future. That horse bolted in the last 24 months. The question is how to maintain security and compliance while GenAI and artificial intelligence agents are putting software code in play.

Every September, National Insider Threat Awareness Month serves as a timely reminder that some of the most damaging security incidents don’t originate from external attackers breaching the perimeter — they come from within. Whether through malicious intent, negligence, or simple human error, insiders with legitimate access to systems, data, and facilities remain one of the most persistent and difficult-to-detect risks facing organizations today. As hybrid work, AI-powered tools, and increasingly complex IT environments reshape the workplace, the insider threat landscape continues to evolve in ways that demand fresh attention from security professionals.

With agentic AI further boosting productivity, human code review becomes a serious bottleneck. Developers need to move upstream, establishing the ground rules to ensure that AI plays by the rules.

​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.