How to catch and fix a Guice dependency injection issue using Sensei
The Sensei project itself has its own set of recipes that have built up over time. This blog post is an example of one of the scenarios the Sensei team built a recipe for. A misconfiguration of Guice, which led to a NullPointerException being reported at runtime during testing.
This can be generalized to many Dependency Injection scenarios where code is syntactically correct, but because the wiring configuration was incorrect, an error slips through.
This often happens when we are learning the technology, and we keep making the simple mistake of forgetting to wire things up. But this also happens to experienced professionals because, well... we all make mistakes, and we may not have Unit Tests to cover everything.

RunTime Exceptions from Incorrect Dependency Injection Wiring
The code below fails at runtime with a NullPointerException.
injector = Guice.createInjector(new SystemOutModule());
CountReporter reporter = injector.getInstance(CountReporter.class);
String [] lines5 = {"1: line", "2: line", "3: line", "4: line", "5: line"};
reporter.reportThisMany(Arrays.asList(lines5));
Assertions.assertEquals(5, reporter.getCount());
The code is syntactically correct but fails because we missed out a requestStaticInjection in our SystemOutModule configuration.
public class SystemOutModule extends AbstractModule {
@Override
protected void configure() {
binder().bind(ILineReporter.class).to(SystemOutReporter.class);
}
}
When we try to use the reporter, created using the Injector, it is not fully instantiated and we receive a NullPointerException when we call reportThisMany.
We may well have missed that in our code review, or we didn't have unit tests that triggered the dependency injection, and it slipped out into our build.
Warning Signs
In this case, there is a warning sign, the CountReporter has a static field annotated with @Inject but... the CountReporter class itself is package private.
In a complicated code base this could be a warning sign that the code is incorrect because the Module class configuring the bindings needs to be in the same package for this to work.
class CountReporter {
@Inject
private static ILineReporter reporter;
Another error that we made, which we might have picked up in a code review, is that we forgot to actually bind the fields in the SystemOutModule configure method.
binder().requestStaticInjection(CountReporter.class);
Had we written the requestStaticInjection code then the Syntax Error generated when trying to use the CountReporter would have alerted us to the simple error.
> 'reporters.CountReporter' is not public in 'reporters'. Cannot be accessed from outside package
Sadly. We forgot, and there were no syntactic warning signs in the code.
How could Sensei help?
We probably wouldn't use Sensei to pick up the missing requestStaticInjection since all our Guice configuration wiring would need to use that method, and we can't guarantee that all wiring is going to be as simple as this use-case.
We could write a Sensei rule to look for some warning signs that our code is not up to scratch.
In this case that would mean:
- Find any classes with @Inject annotated fields
- Where the classes are not public.
The above was the warning sign that they were unlikely to have been wired up.
By creating a recipe, then we will have a warning sign early, during the coding, and reduce the reliance on our pull requests or resolving our tech debt to allow us to add Unit Tests.
How to create a recipe?
The task I want to complete is:
- Create a recipe that matches fields annotated with @Inject which are in protected private classes
That should hopefully give us enough warning to identify any Modules using it and add the missing wiring code.
In my CountReporter class, I will use Alt+Enter to Create a new Recipe and I will start from scratch
I will name this and add a description:
Name: Guice: Injected Field Not Public
Description: If the Injected field is not public then the code might not be wired up
Level: Warning
The search I write looks for a class with a field annotated as Inject but which has not been scoped as public.
search:
field:
with:
annotation:
type: "com.google.inject.Inject"
in:
class:
without:
modifier: "public"

Fix
The QuickFix in the recipe will amend the injected class by changing the scope. But that is not the only code I have to change.
availableFixes:
- name: "Change class to public. Remember to also request injection on this class"
actions:
- changeModifiers:
visibility: "public"
target: "parentClass"

When the recipe is triggered I still have a manual step to perform in my code, adding the line containing requestStaticInjection to fully instantiate the object.
public class SystemOutModule extends AbstractModule {
@Override
protected void configure() {
binder().bind(ILineReporter.class).to(SystemOutReporter.class);
// instantiate via dependency injection
binder().requestStaticInjection(CountReporter.class);
}
}
I could potentially write another recipe to pick this up. I probably wouldn't do that unless forgetting to add the static injection became a semi-regular error that I made when coding.
Summary
If we ever find ourselves making a mistake with a common root pattern, then Sensei can help codify the knowledge around detecting and fixing the issue, and then hopefully, it won't slip through code reviews and into production.
Sometimes the recipes we write identify heuristic patterns i.e. matching them doesn't guarantee that there is a problem, but is likely that there is a problem.
Also, the recipes and QuickFixes that we write, don't have to be fully comprehensive, they need to be good enough that they help us identify and fix problems without being overcomplicated. Because when they become overcomplicated they become harder to understand and harder to maintain.
---
You can install Sensei from within IntelliJ using "Preferences \ Plugins" (Mac) or "Settings \ Plugins" (Windows) then just search for "sensei secure code".
The source code and recipes for this post can be found in the `sensei-blog-examples` repository in the Secure Code Warrior GitHub account, in the `guiceexamples` module.
https://github.com/securecodewarrior/sensei-blog-examples
Controle el desarrollo impulsado por IA antes de su lanzamiento
Mida el riesgo asistido por IA, aplique políticas de codificación segura en el momento de la confirmación y acelere la entrega segura en todo su ciclo de vida de desarrollo de software (SDLC).
Explorar más blogs
Acceda a contenido especializado sobre programación segura, gobernanza de IA y gestión de riesgos de software.

Una cultura de seguridad: cómo Sage creó su programa de defensores
Descubre cómo Sage reforzó su seguridad con un enfoque flexible y centrado en las relaciones, logrando formar a más de 200 expertos en seguridad y alcanzar una reducción de riesgos cuantificable.

Kamer van Koophandel: Seguridad a escala impulsada por los desarrolladores
La Cámara de Comercio (Kamer van Koophandel) comparte cómo integró la programación segura en el desarrollo diario mediante certificaciones basadas en roles, evaluaciones comparativas de puntuación de confianza y una cultura de responsabilidad compartida en seguridad.

Cómo un «Juego de Códigos» guía a IAG Group hacia un futuro de programación más seguro
IAG Group es la entidad detrás de muchas de las principales compañías de seguros en la región de Asia-Pacífico, que suscribe pólizas para millones de clientes por un valor aproximado de 11.400 millones de dólares australianos en primas anuales.

Mes de la Concienciación sobre Ciberseguridad 2026: Comprender la seguridad de la IA es fundamental para la defensa empresarial
Hemos llegado a un punto en el que la mayoría de las principales empresas de IA han pedido públicamente una ralentización global en el desarrollo de la IA para que las medidas de seguridad puedan ponerse al día, pero la verdad es que ya se han materializado graves problemas de seguridad. Esto deja a innumerables líderes de seguridad y equipos ejecutivos en una situación urgente, a medida que los costes monetarios y de riesgo de la implementación de la IA siguen acumulándose.

Habilitador 8: Branding de su programa
Un programa de codificación segura necesita algo más que un buen contenido para tener éxito. El Habilitador 8 muestra cómo el branding transforma la participación en una experiencia codiciada basada en el estatus.
.avif)
Cada empleado está ahora en la primera línea de la ciberseguridad de la IA
El panorama tecnológico empresarial está cambiando a una velocidad que pocos previeron hasta que fue demasiado tarde. Hemos cruzado oficialmente el umbral del código escrito por humanos y la asistencia básica de copilotos hacia la era del Ciclo de Vida de Desarrollo Agéntico (ADLC). Si bien los agentes de IA autónomos prometen una eficiencia sin precedentes en múltiples funciones, también traen consigo una clase completamente nueva de riesgos regulatorios y de seguridad.
Proteja el desarrollo basado en IA antes de su lanzamiento
Identifique riesgos de desarrollo, aplique políticas y prevenga vulnerabilidades en todo el ciclo de vida de su software.